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This Premium Career Track - Chief Technology Officer (CTO) program by Uplatz includes the following courses:

1) Cloud Computing Basics

2) Microsoft Azure Fundamentals

3) Business Intelligence and Data Analytics

4) Tableau (comprehensive)

5) Power BI

6) Python Programming (basic to advanced)

7) R Programming (basic to advanced)

8) Data Science with Python

9) Data Science with R

10) Machine Learning (basic to advanced)

11) Machine Learning with Python

12) Deep Learning Foundation

13) CISSP (Cybersecurity)

14) Introduction to DevOps

15) Angular 8

16) Node.js

17) ReactJS

18) SQL Programming with MySQL

19) Unix and Shell Scripting

20) Google Analytics

21) Microsoft Excel

22) Google Sheets

23) Project Management Fundamentals

24) Microsoft Project (basic to advanced)

25) Leadership and Management

A Chief Technology Officer (CTO) is a high-level executive in an organization responsible for overseeing the technology strategy, implementation, and management. The CTO plays a critical role in aligning technology initiatives with the overall business goals of the organization.

While the specific responsibilities of a CTO can vary depending on the size and nature of the company, their key responsibilities generally include: Technology Strategy, Innovation and Research, Technology Infrastructure, Cybersecurity and Data Privacy, Team Leadership and Development, Vendor Management, Budgeting and Resource Allocation, Technology Governance, Business Continuity and Disaster Recovery, Collaboration with Other Executives, Technology Partnerships and Alliances, Intellectual Property Management, Technology Roadmap, Data Analytics and Business Intelligence, IT Compliance and Risk Management, Technology Scalability, and Stakeholder Management.

The CTO is a strategic leader who plays a crucial role in driving technology initiatives that support the organization's growth, innovation, and success. They must combine technical expertise with business acumen and leadership skills to make informed decisions that align technology with the organization's overall vision and objectives.

Course/Topic 1 - Cloud Computing Basics - all lectures

In this lecture session we learn about cloud computing, which means storing and accessing data over the internet instead of a hard disk. It is defined as a service that provides users to work over the internet.
38:26
In this lecture session we learn about cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale.
30:33
In this lecture session we learn about Cloud computing is a general term for anything that involves delivering hosted services over the internet. These services are divided into three main categories or types of cloud computing.
33:14
In this tutorial we learn about the importance of cloud computing can be found in using services like Google Drive and Apple iCloud. The use of these services allows documents, contacts, pictures, and a whole lot more online.
32:19

Course/Topic 2 - Microsoft Azure Fundamentals - all lectures

In this lecture session we learn about microsoft azure course introduction and also talk about overview of microsoft azure.
21:37
In this lecture session we learn about azure basics functions and importance of microsoft azure.
20:36
In this lecture session we learn about microsoft azure features and also talk about functions of microsoft azure in brief.
29:49
In this lecture session we learn about microsoft azure glossary and also talk about features of azure glossary in microsoft azure fundamentals.
22:08
In this lecture session we learn about Microsoft azure certification path in microsoft azure fundamentals and also talk about features of certification path.
28:48
In this lecture session we learn about azure certification path and also talk about features of microsoft azure in brief.
33:38
In this lecture session we learn about the fundamentals of cloud computing and also talk about the features of cloud.
38:26
In this lecture session we learn about cloud computing functions and also talk about the importance of cloud computing in brief.
30:33
In this lecture session we learn about cloud computing terms and conditions and also talk about features of terms and computing of cloud computing.
33:14
In this lecture session we learn about amazon web service and azure and also talk about the basic difference between amazon web service and microsoft azure.
32:15
In this lecture session we learn about we learn about Getting started with microsoft azure and also talk about features and basic overview of Azure.
17:04
In this lecture session we learn about the advantages of Azure and also talk about the importance of Microsoft azure.
20:51
In this lecture session we learn about the basic advantage of Azure in microsoft fundamentals.
20:23
In this lecture session we learn about features of microsoft azure and also talk about functions of microsoft azure.
28:20
In this lecture session we learn about the advantages of microsoft azure and also talk about factors of microsoft azure.
28:00
In this lecture session we learn about career in microsoft azure and also career in microsoft azure in brief.
38:21
In this lecture session we learn about Microsoft Azure IOT and also talk about features of Azure IOT in brief.
25:04
In this lecture session we learn about fundamentals of azure components in microsoft components and also talk about features of azure components.
31:50
In this lecture session we learn about microsoft azure storage architecture and also talk about functions of azure storage architecture in microsoft azure.
1:03:57
In this lecture session we learn about microsoft azure table storage and also talk about features of azure table storage.
13:04
In this lecture session we learn about azure blob storage and also talk about the importance of microsoft azure blob storage.
14:15
In this lecture session we learn about the advantages of blob storage and also talk about all advantages of blob storage.
13:38
In this lecture session we learn about microsoft azure Queue storage in azure and also talk about features of azure Queue storage in microsoft azure.
17:05
In this lecture session we learn about azure virtual machines in microsoft azure and also talk about the importance of virtual machines.
16:25
In this lecture session we learn about azure mobile app service and also talk about how we develop mobile app services.
35:46
In this lecture session we learn about azure event grid and also talk about features of microsoft azure event grid.
27:10
In this lecture session we learn about microsoft azure backup service in azure cloud and also talk about the importance of microsoft azure backup services.
35:50
In this lecture session we learn about azure event hub and also talk about features of microsoft azure event hub.
31:09
In this lecture session we learn about azure quickstart templates in fundamentals of microsoft azure and also talk about the importance of azure quickstart template.
23:14
In this lecture session we learn about azure API app service in microsoft azure and also talk about functions of azure API app service.
35:33
In this lecture session we learn about azure cloud services and also talk about azure cloud services
39:30
In this lecture session we learn about azure SQL database configuration and also talk about SQL database features.
26:51
In this lecture session we learn about Microsoft Azure devOps and also talk about the importance of azure devOps.
27:29
In this lecture session we learn about azure express route and also talk about microsoft azure express route.
29:18
In this lecture session we learn about Microsoft Azure SQL database in microsoft azure and also talk about features of SQL.
19:59
In this lecture session we learn about microsoft azure key vault in microsoft azure and also talk about key vaults in azure.
25:55
In this lecture session we learn about microsoft azure load balancer in microsoft azure and also talk about azure load balancer.
27:41
In this lecture session we learn about azure CDN in microsoft azure fundamentals and also talk about azure CDN.
17:26
In this lecture session we learn about Microsoft Azure cosmos DB in cloud computing and also talk about features of cloud computing.
30:06
In this lecture session we learn about fundamentals of microsoft azure domain in azure and also talk about the importance of azure domains.
47:11
In this lecture session we learn about legacy application modernization and also talk about features of legacy application modernization.
18:04
In this lecture session we learn about microsoft azure portals and also talk about all portals of microsoft azure.
20:52
In this lecture session we learn about microsoft azure services portal and also talk about features of azure all services.
46:41
In this lecture session we learn about what is the best model in microsoft azure and also talk about best models for enterprise.
21:39
In this lecture session we learn about microsoft azure deep dive and also talk about features of microsoft azure deep dive.
1:02:04
In this lecture session we learn about azure management portal in microsoft azure management function and factors.
24:31
In this lecture session we learn about subscription and billing and also function importance subscription and billing.
44:32
In this lecture session we learn about azure storage services and also talk about functions of azure storage services.
30:38
In this lecture session we learn about creating and configuring azure storage accounts and also talk about functions of creating azure storage accounts.
48:18
In this lecture session we learn about microsoft azure storage account in fundamentals of azure portals.
31:02
In this lecture session we learn about Microsoft Azure Storage account and also talk about features of azure storage.
44:51
In this lecture session we learn about microsoft azure websites and services in azure and also talk about basics of websites and services.
54:27
In this lecture session we learn about factors of websites and services in microsoft azure.
37:40
In this lecture session we learn about validation warnings in microsoft azure.
12:52
In this lecture session we learn about how to develop azure websites and services and also talk about functions of websites and services.
40:01
In this lecture session we learn about what is services protections and DDos protections in microsoft azure.
30:31
In this lecture session we learn about network interface and also talk about functions of network interface.
34:12
In this lecture session we learn about microsoft azure Vnet connectivity and also talk about features of peeing and global peeing.
42:41
In this lecture session we learn about microsoft azure compute services and also talk about functions of features of compute services.
59:12
In this lecture session we learn about creating virtual machines and also talk about functions of creating virtual machines.
32:23
In this lecture session we learn about creating an availability set in Microsoft Azure and also talk about factors of creating an availability set.
19:46
In this lecture session we learn about scaling microsoft azure virtual machines and also talk about functions of scaling azure virtual machines.
26:48
In this lecture session we learn about azure app services and also talk about how we create microsoft azure app services.
59:34
In this lecture session we learn about creating a web application and deploying it and also talk about features of deploying.
31:13
In this lecture session we learn about features of creating a web application and deploying in microsoft azure.
32:36
In this lecture session we learn about microsoft azure mobile app services and also talk about features of mobile app services.
1:00:42
In this lecture session we learn about microsoft azure notification hub and mobile engagement.
27:11
In this lecture session we learn about microsoft azure functions apps and also talk about features of azure functions apps.
21:46
In this lecture session we learn about microsoft azure functions and also talk about functions of microsoft azure functions.
48:17
In this lecture session we learn about microsoft azure API app and API management and also talk about functions of API management in microsoft azure.
38:27
In this lecture session we learn about creating an API using azure portal and also talk about features creating an azure portal.
09:25
In this lecture session we learn about Azure API app services details and also talk about features of API app services.
40:47
In this lecture session we learn about microsoft azure database services and also talk about features of database services.
34:38
In this lecture session we learn about Microsoft Azure SQL database and also talk about features of SQL database.
14:48
In this lecture session we learn about Microsoft Azure SQL database configuration and also talk about features of SQL database.
29:53
In this lecture session we learn about global distribution and partitioning and also talk about features of global distributions.
23:31
In this lecture session we learn about Microsoft Azure SQL data warehouse and also talk about functions of azure SQL data warehouse.
39:16
In this lecture session we learn about cloud computing importance and also talk about functions of cloud computing importance.
32:19
In this lecture session we learn about microsoft azure certification path and also talk about features of azure certification path.
1:46:42

Course/Topic 3 - Business Intelligence and Data Analytics - all lectures

In this lecture session we discuss about Bi concepts, examples and application of business intelligence and data analytics and also cover other concepts of BI.
14:48
In this lecture session we learn about basic concepts of BI and also cover factors of business intelligence in brief.
19:22
In this lecture session we learn about data warehouse data access and data dashboarding and also cover presentation in BI.
24:10
In this lecture session we learn about product database, advertise database and customer demographic database and also cover data analyst concepts.
19:54
In this lecture session we learn about basic introduction of business intelligence and also cover factors of business intelligence in brief.
31:10
In this lecture session we learn about introduction of predictive modeling and also cover functions of predictive modeling in brief.
1:05:08
In this lecture session we learn about data related to customer services and also talk about customer relation databases in brief.
32:37
In this lecture session we learn about introduction of NoSQL and also cover basic functions of NoSQL in business intelligence.
33:46
In this lecture session we learn about graph stores and also talk about the advantages and disadvantages of graph stores in BI.
25:52
In this lecture session we learn about hierarchical clustering in business intelligence and also talk about clustering factors in BI.
29:58
In this lecture session we learn about introduction of salesforce in business intelligence and also talk about some basic uses of salesforce.
34:25
In this lecture session we learn about introduction to NLP and also cover what is natural language processing in artificial intelligence.
18:30
In this lecture session we learn about natural language processing speech to text conversion and also cover the importance of natural language processing.
25:22
In this lecture session we learn about introduction of apache server in business intelligence and also talk about basics of apache server.
44:24
In this lecture session we learn about deep drive into business intelligence and also talk about factors or deep drive in business intelligence.
30:54
In this lecture session we learn about data warehousing in business intelligence and data analytics and also talk about factors and features of data warehousing.
39:54
In this lecture session we learn about types of data in business intelligence and also talk about different types of data in BI.
25:07
In this lecture session we learn about mobile BI and also talk about open source BI software replacing vendor offering.
39:18
In this lecture session we learn about real time BI in business intelligence and also talk about factors of real time BI in brief.
1:35:17
In this lecture session we learn about data analytics comprehensively and also talk about functions of data analytics.
23:43
In this lecture session we talk about data analytics vs business analytics and also talk about the importance of data analytics.
41:04
In this lecture session we learn about Embedded analytics and also talk about functions of Embedded analytics in data analytics.
1:02:55
In this lecture session we learn about collection analytics and also cover the importance of collection analytics.
59:03
In this lecture session we learn about survival analytics and also cover duration analytics in brief.
29:35
In this lecture session we learn about machine learning techniques and also cover the importance and factors of machine learning techniques in business intelligence.
37:34
In this lecture session we learn about geospatial predictive analytics and also talk about functions of geospatial predictive analytics in business intelligence.
1:01:31
In this lecture session we learn about cohort analysis in data analyst and we also cover functions and importance of cohort analysis.
21:36
In this lecture session we learn about data mining in business intelligence and also talk about data mining functions and why we need data mining in business intelligence.
45:40
In these lecture sessions we learn about anomaly detection and also talk about functions of anomaly detection in brief.
1:00:36
In these lecture sessions we learn about statistically sound association and also talk about factors of statistically sound association in business intelligence.
31:29
In this lecture session we learn about cluster analysis. We’ll cover all types of cluster analysis in brief and also cover the importance of cluster analysis in business analysis.
36:21
In this lecture session we learn about DBSCAN in business intelligence and also talk about DBSCAN functions and importance.
59:58
In this lecture session we learn about regression models in business intelligence and also talk about the function of regression models.
31:57
In this lecture session we learn about extraction based summarization in business intelligence and also cover all types of summarization in data analyst.
10:57
In this lecture session we learn about machine learning in BI and also talk about factors and importance of machine learning in brief.
1:00:50
In this lecture session we learn about machine learning vs BI we also discuss the basic difference between machine learning and business intelligence.
1:15:37
In this lecture session we learn about how ml can make BI better and also talk about ml basic functions.
1:18:01
In this lecture session we learn about data warehousing and also talk about how we manage data warehousing in business intelligence.
18:28
In this lecture session we learn about data warehousing in business intelligence and data analytics and also talk about factors and features of data warehousing.
29:22
In this lecture session we learn about data mart in business intelligence and also talk about data mart function.
32:40
In this lecture session we learn about data dimensions in business intelligence and also cover all types of data dimension in BI.
30:31
In this lecture session we learn about data dimension in business intelligence and also cover functions and importance of data dimension.
24:02
In this lecture session we learn about data vault modeling in business intelligence and also cover different types of vault modeling in brief.
29:14
In this lecture session we learn about links and satellites and also cover the importance and factors of links and satellites in business intelligence.
28:59

Course/Topic 4 - Tableau (comprehensive) - all lectures

In this session you will learn about the Business intelligence (BI) which combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations to make more data-driven decisions
17:31
In this session we will introduce you about Tableau which is a widely used business intelligence (BI) and analytics software trusted by companies like Amazon, Experian, and Unilever to explore, visualize, and securely share data in the form of Workbooks and Dashboards. With its user-friendly drag-and-drop functionality it can be used by everyone to quickly clean, analyze, and visualize your team’s data.
33:45
This session is all about the history of Tableau which was founded by Pat Hanrahan, Christian Chabot, and Chris Stolte from Stanford University in 2003. The main idea behind its creation is to make the database industry interactive and comprehensive.
21:38
In this tutorial, we will discuss the Tableau interface and understand its functioning in detail. Followed by the general understanding of Tableau’s working. Along with this, we will learn the Components of Tableau Server.
34:10
In this session, you will get to know how to use Tableau Prep Builder to clean and prepare your data, start a new flow by connecting to your data, just like in Tableau Desktop. You can also open an existing flow and pick up where you left off.
43:54
In this video, once you have chosen the best Tableau product for you, it is time to start finding insights in your data! Much like Tableau’s suite of products, data connections come in many shapes and sizes. As of this writing, Tableau Desktop: Personal has four different types of data connections, and Tableau Desktop.
33:13
This session teaches you about the Data blending which is a method for combining data from multiple sources. Data blending brings in additional information from a secondary data source and displays it with data from the primary data source directly in the view.
30:50
If you are connected to a data source that has been modified, you can immediately update Tableau Desktop with the changes by selecting a data source on the Data menu and then selecting Refresh.
41:22
In this Tableau tutorial, we are going to study about what is sorting in Tableau. We will also discuss how to use Quick Sort in Tableau. At last, we will see why is my king broken and combined filed. Tableau sort is the process of arranging or ordering the data in Ascending Order or Descending Order.
19:38
In this video, we will show you How to perform sorting in Tableau reports with example. For this Tableau sort demo, we are going to use the report we created in our previous article.
13:43
In this tutorial, we will show you How to perform grouping in Tableau reports with example. For this Tableau Grouping demo, we are going to use the report we created in our previous article. Tableau Grouping is the process of merging or combining two or more values for further analysis.
12:18
In this video, we will show you How to perform grouping in Tableau reports with example? For this Tableau Grouping demo, we are going to use the report we created in our previous video.
24:55
In this video, we will show you how to create Tableau Set, Constant Sets, and Computed Sets. First, Drag and Drop the State Name from Dimension Region to Rows Shelf and Profit from Measures region to Columns Shelf.
26:50
In addition to a Set Action, you can also allow users to change the membership of a set by using a filter-like interface known as a Set Control, which makes it easy for you to designate inputs into calculations that drive interactive analysis. For details, see Show a set control in the video.
38:06
In this session you begin filtering data in Tableau, it's important to understand the order in which Tableau executes filters in your workbook. Filtering is an essential part of analyzing data. This article describes the many ways you can filter data from your view. It also describes how you can display interactive filters in the view, and format filters in the view.
26:07
In this video you will get to know about filtering which is an essential part of analyzing data. This article describes the many ways you can filter data from your view. It also describes how you can display interactive filters in the view, and format filters in the view.
20:49
In this tutorial, we will learn about another interesting and useful feature of Tableau that is Tableau parameters. Here, we will try and gain a good understanding of the parameters in Tableau and their use in Tableau. We will start by discussing the definition of parameters followed by learning how to create parameters and use them in Tableau.
31:36
In this session you will understand how to use parameter actions to let your audience change a parameter value through direct interaction with a viz, such as clicking or selecting a mark. You can use parameter actions with reference lines, calculations, filters, and SQL queries, and to customize how you display data in your visualizations.
24:43
In this Tableau tutorial, we will study What is Tableau Reference Lines, functions of Reference lines in Tableau and the steps involved in creating / Adding reference lines to the Tableau Bar Chart. At last, we will how to create reference lines in Tableau with example. So, let us start Tableau Reference Lines.
20:42
In the tutorial you will get to know how to show trend lines in a visualization to highlight trends in your data. You can publish a view that contains trend lines, and you add trend lines to a view as you edit it on the web. When you add trend lines to a view, you can specify how you want them to look and behave.
25:39
In this Tableau tutorial, you will learn about the story which is a sequence of visualizations that work together to convey information. You can create stories to tell a data narrative, provide context, demonstrate how decisions relate to outcomes, or to simply make a compelling case.
23:15
In this session you will understand how to Use stories to make your case more compelling by showing how facts are connected, and how decisions relate to outcomes. You can then publish your story to the web or present it to an audience. Each story point can be based on a different view or dashboard, or the entire story can be based on the same visualization seen at different stages, with different filters and annotations.
41:34
In this video, we will show you, How to Format Tableau Dashboard Layout with an example. For this, we are going to use the below-shown dashboard. Once you created your dashboard (added required Sheets), you can use the layout tab to format those Sheets or Items as per your requirements.
23:52
Tableau Layout Containers control the spacing between dashboard components. They allow you to format common elements and move multiple dashboard objects at the same time. 
36:38
In our last Tableau tutorial, we discuss How to Format Tableau Dashboard Layout. Here, in this tutorial, we are going to learn about How to Tableau Interactive Dashboard with Data Granularity, Interactivity, and Intuitiveness in Tableau. In other word or in general words we can call this playing with maps in a tableau. so, let us start with How to Create Tableau Interactive Dashboard.
29:40
This tutorial walks you through some of the most common tasks you might perform when creating maps in Tableau. You’ll learn how to connect to and join geographic data; format that data in Tableau; create location hierarchies; build and present a basic map view; and apply key mapping features along the way. If you're new to building maps in Tableau, this a great place to start.
07:55
This tutorial describes how to create and use calculated fields in Tableau using an example. You'll learn Tableau calculation concepts, as well as how to create and edit a calculated field. You will also learn how to work with the calculation editor, and use a calculated field in the view. If you're new to Tableau calculations or to creating calculated fields in Tableau, this is a good place to start.
21:08
You can build several different types of maps for your geographic analysis in Tableau. If you're new to maps, or simply want to take advantage of the built-in mapping capabilities that Tableau provides, you can create a simple point or filled (polygon) map.
13:07
You can always customize a table calculation by editing it in the Table Calculations dialog box, but there are other, more specialized ways to customize a table calculation.
14:15
This video introduces the basics of understanding calculations in Tableau. In this topic, you'll learn why and when to use calculations.
14:17
This session explains the types of LOD expressions you can use in Tableau, as well as when to use them, and how to format them. It also uses an example to demonstrate how to create a simple LOD expression. Level of Detail expressions (also known as LOD expressions) allow you to compute values at the data source level and the visualization level. However, LOD expressions give you even more control on the level of granularity you want to compute.
27:50
To edit a table calculation Right-click the measure in the view with the table calculation applied to it and select Edit Table Calculation. In the Table Calculation dialog box that appears, make your changes.
18:31
Tableau can create interactive visualizations customized for the target audience. In this tutorial, you will learn about the measures, chart types and its features.
15:18
When you save a level of detail expression, Tableau adds it to either the Dimensions or the Measures area in the Data pane. FIXED level of detail expressions can result in measures or dimensions, depending on the underlying field in the aggregate expression.
37:12
In this Tableau tutorial, we are going to learn about using a Histogram in Tableau. Here, we will find answers to questions like what is a histogram, and how do we create it in our Tableau software.
16:11
In this tutorial, 'Sample-Superstore.csv' is used for the demonstration. You can connect to the data source and follow the steps given in the tutorial. Tableau can create interactive visualizations customized for the target audience. In this tutorial, you will learn about the measures, chart types and its features.
25:01
In this Tableau Tutorial, we are going to learn about an interesting chart that is a bubble chart or packed bubble chart. Here, we will learn how to create a bubble chart in Tableau in a stepwise manner. You can create your first Tableau bubble chart with us on your own device. All you need, as of now is a sample data set and Tableau software in your device.
09:54
A histogram is a chart that displays the shape of a distribution. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins.
11:51
Tableau Bubble Chart is used to display the data in circles. We can define each bubble using any of our Dimension members and size by Measure value.
09:54
In this tutorial we will learn about Tree maps which are the relatively simple data visualization that can provide insight in a visually attractive format. Use packed bubble charts to display data in a cluster of circles. Dimensions define the individual bubbles, and measures define the size and color of the individual circles.
10:42
In this Video we will get to know about the best practices which are key to developing informative visualizations that drive your audience to act. A dashboard is successful when people can easily use it to derive answers. Even a beautiful dashboard with an interesting data source could be rendered useless if your audience can’t use it to discover insights.
48:07

Course/Topic 5 - Power BI - all lectures

Learn how you can leverage Power BI to easily build reports and dashboards with interactive visualizations and see how other organizations have used this solution to drive business results with actionable insights.
20:51
In this session, with Power BI Desktop, you can build advanced queries, models, and reports that visualize data. You can also build data models, create reports, and share your work by publishing to the Power BI service.
01:57
This is the first part of Basic Dashboard in Power BI. In this video you will learn how to create a basic dashboard with simple data points.
23:35
In this Video, we will show you how can you install Power PI desktop in PC.
18:05
The third part in a series of Microsoft Power BI tutorials for beginners. This tutorial cover Filter’s pane and the Slicers.
30:14
In this Part 4, video shows the time slicer feature of Power BI Desktop. Also running some simple statistics using the matrix visualization.
30:09
In this Part 5 session you will learn about how to create a simple R script in Power BI desktop using the grid Extra package for displaying data and the dplyr package for data munging.
21:32
In this Microsoft Power BI video, you will learn how to represent the data in a Map using Power BI. For this purpose, a data that contains the columns such as a State, Province, Country, City, ZIP Code/Postal Code, etc. must be present in the database
33:52
In this video you can explore, what is Star Schema, why it is important in Power BI, Among the most basic design skills in designing a data warehouse solution is the star schema design.
09:10
In this Power BI Tutorial, you will look at how to use Power Query in Power BI Desktop to merge different queries and join kind. This Microsoft Power BI tutorial for beginners is aimed at new Power BI users.
07:49
In this video we will go through the basics of data modelling in Power BI, to get you started fast and easy.
01:52
In this video, learn how to use relationship’s view, what other views exist in Power BI Desktop and why it's important to use them.
10:39
This video explains the importance of cross filter direction in Microsoft Power BI. It discusses how the single or bi-directional filter affects the data in the report.
12:44
In this video you will see details about m language and dax language.
16:22
In this video you will learn how to create two interactive Power BI dashboards, plus a decomposition tree using the free Power BI tools.
26:35
In this video, we will show you how you can use a parameter, within a Power BI report, to dynamically change the data in a report.
15:46

Course/Topic 6 - Python Programming (basic to advanced) - all lectures

This video comprehends the terms Python which is to develop by Guido van Rossum. Guido van Rossum started implementing Python in 1989. Python is a very simple programming language so even if you are new to programming, you can learn python without facing any issues.
21:04
This topic will cover, Installing Python which is generally easy, and nowadays many Linux and UNIX distributions include a recent Python. Even some Windows computers now come with Python already installed.
34:34
In this Python tutorial, we will learn about Python variables and data types which is being used in Python. We will also learn about converting one data type to another in Python and local and global variables in Python. So, let’s begin with Python variables and data types Tutorial.
30:53
In this topic you will learn about the data type which is an important concept. Variables can store data of different types, and different types can do different things.
45:15
This session will teach you about the Python defines type conversion functions to directly convert one data type to another which is useful in day to day and competitive programming. This article is aimed at providing information about certain conversion functions.
31:11
In this tutorial, you will learn about the keywords which is the reserved words in Python and identifiers names given to variables, functions, etc. We cannot use a keyword as a variable name, function name or any other identifier. They are used to define the syntax and structure of the Python language.
40:45
In this tutorial, we are going to learn how to take multiple inputs from the user in Python. The data entered by the user will be in the string format. So, we can use the split method to divide the user entered data.
33:57
This tutorial focuses on two built in functions print and input to perform Input and Output task in Python. Also, you will learn to import modules and use them in your program. Some of the functions like input and print are widely used for standard input and output operations respectively. Let us see the output section first.
54:08
This tutorial covers the different types of operators in Python, operator overloading, precedence and associativity. Just like in mathematics, programming languages like Python have operators. You can think of them as extremely simple functions that lie at the basis of computer science.
35:15
In this tutorial, you'll learn everything about different types of operators in Python, their syntax and how to use them with examples. Operators are special symbols in Python that carry out arithmetic or the logical computation. The value that the operator operates on is called the operand.
31:05
Previously, in our tutorial on Python Operators., Today, in this Python Bitwise Operators Tutorial, we will discuss Python Bitwise AND, OR, XOR, Left-shift, Right-shift, and 1’s complement Bitwise Operators in Python Programming. Along with this, we will discuss syntax and example of Python Bitwise Operators.
44:28
Today, we talk about Python decision making constructs. This includes Python if statements, if else statements, elif statement, nested if conditions and single statement conditions. We will understand these with syntax and example to get a clear understanding. So, let’s start the Python Decision Making Tutorial.
37:10
In this session you will learn about the if elif else which are conditional statements that provide you with the decision making that is required when you want to execute code based on a particular condition. The if elif else statement used in Python helps automate that decision making process.
30:46
In this session, you'll learn the different variations of for loop, for loop is used for iterating over a sequence that is either a list, a tuple, a dictionary, a set, or a string. This is less like the for keyword in other programming languages, and works more like an iterator method as found in other object-orientated programming languages.
37:25
In this session, you will learn to create a while loop in Python. Loops are used in programming to repeat a specific block of code. In this article, you will learn to create a while loop in Python. Loops are used in programming to repeat a specific block of code.
38:54
In this session, we show how to create an infinite loop in Python. An infinite loop that never ends it never breaks out of the loop. So, whatever is in the loop gets executed forever, unless the program is terminated. For certain situations, an infinite loop may be necessary.
38:57
In this video, you will learn how to make the computer execute a group of statements over and over if certain criterion holds. The group of statements being executed repeatedly is called a loop.
29:04
In this session, you'll learn about the different numbers used in Python, how to convert from one data type to the other, and the mathematical operations supported in Python. Python supports integers, floats and complex numbers.
43:57
In the tutorial on strings in Python, you learned how to define strings objects that contain sequences of character data. Processing character data is integral to programming. It is a rare application that doesn’t need to manipulate strings at least to some extent.
23:30
As discussed in the above tutorial, strings in Python are immutable and thus updating or deleting an individual character in a string is not allowed, which means that changing a particular character in a string is not supported in Python. Although, the whole string can be updated and deleted.
55:48
In this session, we'll learn everything about Python lists, how they are created, slicing of a list, adding or removing elements from them and so on. The list is a most versatile datatype available in Python which can be written as a list of comma-separated values items between square brackets. Important thing about a list is that items in a list need not be of the same type.
44:43
In this tutorial, learn how to update list element using Python. Use the index position and assign the new element to change any element of List. You can change the element of the list or item of the list with the methods given here.
39:20
In that tutorial of Python Functions, we discussed user-defined functions in Python. But that isn’t all, a list of Python built-in functions that we can toy around with. In this tutorial on Built-in functions in Python, we will see each of those, we have 67 of those in Python 3.6 with their Python Syntax and examples.
24:00
In this tutorial, you'll learn everything about Python tuples. More specifically, what are tuples, how to create them, when to use them and various methods you should be familiar with. A tuple in Python is similar to a list. The difference between the two is that we cannot change the elements of a tuple once it is assigned whereas we can change the elements of a list.
34:37
This session teaches you the tuple in Python which are immutable sequences, you cannot update them. You cannot add, change, remove items (elements) in tuples.Tuple represent data that you don't need to update, so you should use list rather than tuple if you need to update it. However, if you really need to update tuple, you can convert it to list, update it, and then turn it back into tuple.
39:57
In this tutorial, you'll learn everything about Python dictionaries how they are created, accessing, adding, removing elements from them and various built in methods. Python dictionary is an unordered collection of items. Each item of a dictionary has a pair. Dictionaries are optimized to retrieve values when the key is known.
52:22
In this session we will teach you the dictionary which is a data type similar to arrays, but works with keys and values instead of indexes. Each value stored in a dictionary can be accessed using a key, which is any type of object a string, a number, a list, etc. instead of using its index to address it.
34:32
In this session we will teach you the Python for beginners training course which is a lead the students from the basics of writing and running Python scripts to more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting.
38:11
In this video, you will learn to manipulate date and time in Python with the help of examples. Python has a module named datetime to work with dates and times. Let's create a few simple programs related to date and time before we dig deeper.
26:48
In this session, you'll learn about functions, what a function is, the syntax, components, and types of functions. Also, you'll learn to create a function in Python. In Python, a function is a group of related statements that performs a specific task. Functions help break our program into smaller and modular chunks.
42:07
In this video we will learn, the function which use the same variable and object. Pass by Value. In pass by value the function is provided with a copy of the argument object passed to it by the caller. That means the original object stays intact and all changes made are to a copy of the same and stored at different memory locations.
28:54
In this tutorial, you'll learn about the anonymous function, also known as lambda functions. You'll learn what they are, their syntax and how to use them with examples.
31:23
In this tutorial we will teach you the module which is a piece of software that has a specific functionality. Like, when building a ping pong game, one module would be responsible for the game logic, and another module would be responsible for drawing the game on the screen. Each module is a different file, which can be edited separately.
31:39
This session teaches you the Python rename method which is used to rename a file or directory. This method is a part of the python module and comes extremely handy.
37:02
In this tutorial, you'll learn about Python file operations. More specifically, opening a file, reading from it, writing into it, closing it, and various file methods that you should be aware of.
34:35
In this tutorial we will learn about program for files in Python which provides us with an important feature for reading data from the file and writing data into a file. Mostly, in programming languages, all the values or data are stored in some variables which are volatile in nature.
36:20
In this session we will tell you the method that you the current position within the file; in other words, the next read or write will occur at that many bytes from the beginning of the file. The seek method changes the current file position.
38:05
In this tutorial, you'll learn how to handle exceptions in your Python program using try, except and finally statements with the help of examples. Python has many built-in exceptions that are raised when your program encounters an error (something in the program goes wrong).
38:08
In this tutorial, you will learn about different types of errors and exceptions that are built-in to Python. They are raised whenever the Python interpreter encounters errors.
42:46
In this video we will teach you about the Exception handling in Python which is very similar to Java. The code, which harbors the risk of an exception, is embedded in a try block.
31:27
In this tutorial, you will learn about the core functionality of Python objects and classes. You'll learn what a class is, how to create it and use it in your program.
38:34
In this session you will learn about the programming in Python (object-oriented programming) for some time, then you have definitely come across methods that have self as their first parameter. Let us first try to understand what this recurring self-parameter is.
42:03
This tutorial teaches you about the regular expression which is a special sequence of characters that helps you match or find other strings or sets of strings, using a specialized syntax held in a pattern. Regular expressions are widely used in UNIX world.
46:36
In this tutorial we will learn about the python search which is a method of the module That is Syntax of search () re. search (pattern, string). It is similar to re. match () but it doesn’t limit us to find matches at the beginning of the string only. Unlike in re. match () method, here searching for pattern ‘Tutorials’ in the string ‘TP Tutorials Point TP’ will return a match.
53:36
This workshop will introduce GUI programming in Python, it is a is a popular language for elementary programming but it not so easy to write programs with a graphical user interface (GUI).
28:07
In this tutorial, we will learn how to develop graphical user interfaces by writing some Python GUI examples using the Tkinter package. Tkinter package is shipped with Python as a standard package, so we don’t need to install anything to use it.
41:04
This session teaches you about the frame widgets which is a rectangular region on the screen. The frame widget is mainly used as a geometry master for other widgets, or to provide padding between other widgets.
46:10

Course/Topic 7 - R Programming (basic to advanced) - all lectures

In this lecture session we learn about basic introduction to R programming and also talk about some key features of R programming.
16:58
In this lecture session we learn about the setup of R language in your system and also talk about the importance of R programming.
24:13
In this lecture session we learn about variables and data types in R language and also talk about types of variables and data types in R programming.
31:36
In this lecture session we learn about uses of variable and data types in our programs and also talk about some key features of variables and data types.
29:16
In this lecture session we learn about input - output features and also talk about features of input - output features.
38:05
In this lecture session we learn about posted function () in input output features and also talk about features of posted functions().
25:43
In this lecture session we learn about operators in R and also talk about features of operators in R programming.
34:16
In this lecture session we learn about different types of operators in R language and also talk about features of all types of operators in R.
29:19
In this lecture session we learn about vectors in data structure in R programming and also talk about features of vectors in data structures in brief.
32:29
In this lecture session we learn about the importance of vectors in data structure and also talk about vectors in data structures in brief.
30:29
In this lecture session we learn about list data structure in R programming and also talk about features of list in data structure.
33:47
In this lecture session we learn about more operations on the list and also talk about features of List in data structures in brief.
29:10
In this lecture session we learn about matrix in R programming and also talk about features of matrix in data structure in R language.
43:57
In this lecture session we learn about matrix in R programming and also talk about features of matrix in data structure in R language.
25:15
In this lecture session we learn about matrix data structure in R programming and also talk about some key features of matrix and data structure.
09:36
In this lecture session we learn about arrays in R programming and also talk about features of arrays.
31:56
In this lecture session we learn about different types of arrays in data structure and also talk about features of Arrays in data structure in brief.
38:35
In this lecture session we learn about data frame in R programming and also talk about function of data frame.
43:06
In this lecture session we learn about data frame features in R programming and also talk about the importance of data structure.
33:59
In this lecture session we learn about the importance of Data frame in brief and also talk about function of data frame in R programming.
31:20
In this lecture session we learn about data frame key features of data frame in data structure in brief.
19:40
In this lecture session we learn about factors data structures in R programming and also talk about the importance of factors.
34:09
In this lecture session we learn about factors of data structure in R programming and also talk about different types of factors in R language.
17:14
In this lecture session we learn about decision making in R programming and also talk about features of decision making in R.
32:52
In this lecture session we learn about different types of decision making statements and also talk about features of all decision statements.
15:53
In this lecture session we learn about decision making using integers and also talk about functions of integers.
30:02
In this lecture session we learn about Loops in R programming and also talk about factors of Loops in R language.
28:28
In this lecture session we learn about functions of Loops and why we need Loop statement in R programming and also talk about key features of Loop statement.
32:03
In this lecture session we learn about different types of Loops in R programming and also talk about features of For loop, while loop and do while loop.
25:29
In this lecture session we learn about functions in R programming language and also talk about features of functions in R language.
37:42
In this lecture session we learn about different types of functions in R programming and also talk about the importance of functions.
34:11
In this lecture session we learn about string in R programming and also talk about features of string function in R.
25:18
In this lecture session we learn about why we need strings in R programming and also talk about the importance of strings.
26:51
In this lecture session we learn about packages in R programming and also talk about features of packages in R.
35:17
In this lecture session we learn about data and file management in R programming and also talk about functions of data and file management.
32:45
In this lecture session we learn about how we manage the data and file in R programming and also talk about the importance of data and file management.
23:18
In this lecture session we learn about Line chart in R programming and also talk about features of line chart in brief.
33:06
In this lecture session we learn about scatterplot in R language and also talk about functions of scatters plot.
26:38
In this lecture session we learn about Pie chart in R programming and also talk about features of Pie Chart in brief.
33:32
In this lecture session we learn about bar charts in R language and also talk about features of Bar chart in brief.
09:43
In this lecture session we learn about how we use bar charts in R programming and also talk about features of Bar charts.
29:50
In this lecture session we learn about histogram in R programming and also talk about features of histogram.
26:34
In this lecture session we learn about Boxplots in R programming and also talk about features of Boxplot in R language.
21:49

Course/Topic 8 - Data Science with Python - all lectures

In this video tutorial we will get introduced to Data Science and the integration of Python in Data Science. Furthermore, we will look into the importance of Data Science and its demand and the application of Data Science.
1:01:14
In this video we will learn, all the concepts of Python programming related to Data Science. We will also learn about the Introduction to Python Programing, what is Python Programming and its History, Features and Application of Python along with its setup. Further we will see how to get started with the first python program.
59:19
This video talks about the Variable and Data Types in Python Programming. In this session we will learn What is variable, the declaration of variable and variable assignment. Further we will see the data types in python, checking data types and data type conversions.
27:05
This tutorial will help you to understand Data Types in python in depth. This video talks about the data types such as numbers, sequence type, Boolean, set and dictionary.
55:27
This tutorial talks about the Identifier, keyword, reading input and output formatting in Data Science. We will learn about what is an identifier and keywords. Further we will learn about reading input and taking multiple inputs from a user, Output formatting and Python end parameter.
49:19
This tutorial talks about taking multiple inputs from user and output formatting using format method, string method and module operator.
44:09
This tutorial talks about the Operators and type of operators. In this session we will learn about the types of operators such as arithmetic, Relational and Assignment Operators.
27:52
This tutorial talks further about the part 2 of operators and its types. In this session we will learn about the types of operators such as Logical, Membership, Identity and Bitwise Operators.
31:22
In this video you will learn about the process of decision making in Data Science. Furthermore, this tutorial talks about different types of decision-making statements and its application in Data Science.
45:23
In this video tutorial we will learn about the Loops in Python programing. We will cover further the different types of Loops in Python, starting with: For Loop.
32:47
In this session we will cover the further part of loops in Python programming. The type of loops explained in this video is: While loop and nested loop.
39:43
In this session we will cover the further part of loops in Python programming. The type of loops explained in this video is: break, continue and pass loops
23:13
In this video tutorial we will start explaining about the lists in Python Programming. This tutorial talks about accessing values in the list and updating the list in Data Science.
46:54
In this video tutorial we will look into the further parts about the lists in Python Programming. Deleting list elements, basic list operations, built in functions and methods and the features which are covered in this session.
40:30
This tutorial will cover the basics on Tuples and Dictionary function in Data Science. We will learn about accessing and deleting tuple elements. Further we will also cover the basic tuples operations and the built in tuple functions and its methods. At the end we will see the differences in list and tuple.
53:32
This tutorial will cover the advanced topics on Tuples and Dictionary function in Data Science. Further in this session we will learn about the Python Dictionary, how to access, update and delete dictionary elements. Lastly we will cover built in functions and methods.
51:22
In this session we will learn about the functions and modules used in Data science. After watching this video, you will be able to understand what is a function, the definition of function and calling a function.
44:01
In this session we will learn about the further functions and modules used in Data science. After watching this video, you will be able to understand the ways to write a function, Types of functions, Anonymous Functions and Recursive functions.
43:16
In this session we will learn about the advanced functions and modules used in Data science. After watching this video, you will be able to understand what is a module, creating a module, import statement and locating modules.
48:21
This tutorial talks about the features of working with files. In this video we will learn about opening and closing file, the open function, the file object Attributes, the close method, reading and writing files.
1:05:09
This tutorial talks about the advanced features of working with files. In this video we will learn about file positions, renaming and deleting files.
26:50
In this session we will learn about the regular expression. After this video you will be able to understand what is a regular expression, meta characters, match function, search function, Re- match vs research, split function and sub function.
1:02:45
This video introduces you to the Data Science Libraries. In this video you will learn about the Data science libraries: libraries for data processing, modelling and data visualization.
45:35
In this session we will teach about the components of python ecosystem in Data Science. This video talks about the Components of Python Ecosystem using package Python distribution Anaconda and jupyter notebook.
54:24
This tutorial talks about the basics of analyzing data using numpy and pandas. The Pandas module mainly works with the tabular data, whereas the NumPy module works with the numerical data. We will further see what is Numpy and why we use numpy.
56:58
This tutorial talks about the later part of analyzing data using numpy and pandas. In this tutorial we will learn how to install numpy.
43:37
This tutorial talks about the advanced part of analyzing data using numpy and pandas. In this session we will learn what is Pandas and the key features of Pandas. We will also learn about the Python Pandas environment setup.
37:21
This tutorial talks about the advanced part of analyzing data using numpy and pandas. In this session we will learn about Pandas data structure with example.
1:12:53
This the last session on Analysing Data using Numpy and Pandas. In this session we will learn data analysis using Pandas
28:31
In this video tutorial we will learn about the Data Visualization using Matpotlib. This video talks about what is data visualisation, introduction to matplotlib and installation of matplotlib.
37:45
In this session we will see the part 2 of Data Visualization with Matplotlib. This video talks about the types of data visualization charts and line chart scatter plot
43:41
This tutorial covers part 3 of Data Visualization with Matplotlib. This session covers the types of data visualisation charts: bar chart histogram, area plot pie chart and box plot contour plot.
1:09:26
This session talks about the Three-Dimensional Plotting with Matplotlib . In this we will learn about plot 3D scatter, plot 3D contour and plot 3D surface plot.
1:03:43
In this tutorial we will cover basics of Data Visualisation with Seaborn. Further we will cover Introduction to seaborn, seaborn functionalities, how to install seaborn and the different categories of plot in seaborn
41:53
In this tutorial we will cover the advanced topics of Data Visualisation with Seaborn. In this video we will see about exploring seaborn plots.
59:16
Introduction to Statistical Analysis is taught in this video. We will learn what is statistical analysis and introduction to math and statistics for data science. Further we will learn about the terminologies in statistics for data science and categories in statistics, its correlation and lastly mean median and mode quartile.
1:15:05
This video course talks about the basics of Data Science methodology. We will learn how to reach from problem to approach.
47:33
In this session we will see Data Science Methodology from requirements to collection and from understanding to preparation.
44:12
In this session we will learn advanced Data Science Methodology from modelling to evaluation and from deployment to feedback.
39:25
This video tutorial talks about the - Introduction to Machine Learning and its Types. In this session we will learn what is machine learning and the need for machine learning. Further we will see the application of machine learning and different types of machine learning. We will also cover topics such as supervised learning, unsupervised learning and reinforcement learning.
56:17
This video tutorial talks about the basics of regression analysis. We will cover in this video linear regression and implementing linear regression.
1:11:51
This video tutorial talks about the further topics of regression analysis. In this video we will learn about multiple linear regression and implementing multiple linear regression.
54:25
This video tutorial talks about the advanced topics of regression analysis. In this video we will learn about polynomial regression and implementing polynomial regression.
38:18
In this session we will learn about the classification in Data science. We will see what is classification, classification algorithms and Logistic regression. Also we will learn about implementing Logistic regression.
1:08:43
In this session we will learn about the further topics of classification in Data science, such as decision tree and implementing decision tree.
38:36
In this session we will learn about the advanced topics of classification in Data science, such as support vendor machine and implementing support vector machine.
25:37
This tutorial will teach you about what is clustering and clustering algorithms. Further we will learn what K means clustering and how does K means clustering work and also about implementing K means clustering.
53:10
In this session we will see the further topics of clustering, such as hierarchical clustering, agglomerative hierarchical clustering, how does agglomerative hierarchical clustering Work and divisive hierarchical clustering.
28:55
This video tutorial talks about the advanced topics of clustering, such as implementation of agglomerative hierarchical clustering.
33:58
This video will help you to understand basics of Association rule learning. In this session we will learn about the Apriori algorithm and the working of Apriori algorithm.
53:30
This video will help you to understand advanced topics of Association rule learning such as implementation of Apriori algorithm.
58:45
This is a session on the practical part of Data Science application. In this example we will see problem statement, data set, exploratory data analysis.
56:40
This is a session on the practical part of Data Science application.
42:39
This is a session on the practical part of Data Science application. In this we will see the implementation of the project.
50:54
This is a session on the practical part of Data Science application
38:18
This is a session on the practical part of Data Science application
1:02:31

Course/Topic 9 - Data Science with R - all lectures

In this lecture session we learn about introduction of data science and also talk about features of data science in R.
54:03
In this lecture session we learn about data collection and management and also talk about features of data collection and management in data science with R.
29:32
In this lecture session we learn about model deployment and maintenance and also talk about functions of model deployment and maintenance in data science with R.
12:47
In this lecture session we learn about setting expectations and also talk about factors of setting expectations in brief.
10:18
In this lecture session we learn about loading data into R and also talk about features of loading data into R and also talk about the importance of loading data into R.
42:20
In this lecture session we learn about exploring data in data science and machine learning and also talk about features of exploring data in data science and machine learning.
08:01
In this lecture session we learn about features of exploring data using R and also talk about factors of exploring data using R.
45:36
In this lecture session we learn about benefits of data cleaning and also talk about features of benefits of data cleaning.
22:44
In this lecture session we learn about cross validation in R and also talk about features of validation in data science with R.
17:32
In these lecture sessions we learn about data transformation in data science with R and also talk about features of data transformation in brief.
1:35:26
In this lecture session we learn about modeling methods in data science with R and also talk about the importance of modeling methods.
20:13
In this lecture session we learn about solving classification problems and also talk about features of solving classification problems in brief.
11:55
In this lecture session we learn about working without known targets in data science with r and also talk about features of working without known targets.
19:58
In this lecture session we learn about evaluating models in data science with R and also talk about features of evaluating models in brief.
28:11
In this lecture session we learn about confusion matrix in indian accounting standards and also talk about features of confusion matrix.
34:03
In this lecture session we learn about introduction to linear regression and also talk about features of linear regression in indian accounting standards.
1:25:24
In this lecture session we learn about linear regression in R and also talk about features and functions of linear regression in brief.
26:51
In this lecture session we learn about linear regression in R in data science with r and also talk about features of linear regression in R language.
41:22
In this lecture session we learn about simple and multiple regression in data science with r and also talk about the basic difference between simple and multiple regression in brief.
56:54
In this lecture session we learn about linear and logistic regression in data science with r language and also talk about functions of linear and logistics regressions.
29:09
In this lecture session we learn about support vector machines (SVM) in R and also talk about features of support vector machines in data science with R language.
45:18
In this lecture session we learn about factors of support vectors machines in data science with R and also talk about features of support vectors machines.
1:30:55
In this lecture session we learn about unsupervised methods in data science with R and also talk about functions of unsupervised methods in data science.
24:44
In this lecture session we learn about clustering in data science with R language and also talk about features of clustering in data science.
50:44
In this lecture session we learn about K-means algorithms in R and also talk about all types of algorithms in data science with R language.
1:09:44
In this lecture session we learn about hierarchical clustering in data science with R language and also talk about features of hierarchical clustering.
33:41
In this lecture session we learn about libraries in data science with R and also talk about libraries of hierarchical clustering in brief.
23:15
In this lecture session we learn about the dendrogram of diana and also talk about all types of clustering in data science with R.
41:05
In this lecture session we learn about market basket analysis in data science with R and also talk about features of market basket analysis in data science with R.
05:08
In this lecture session we learn about MBA and association rule mining in data science with r language.
23:52
In this lecture session we learn about implementing MBA in data science with R and also talk about implementing MBA.
09:18
In this lecture session we learn about association rule learning in data science with R and also talk about features of association rule learning.
24:02
In this lecture session we learn about decision tree algorithms in data science with R and also talk about features of tree algorithms.
36:29
In this lecture session we learn about exploring advanced methods in tree algorithms in data science with R and also talk about features of exploring advanced methods.
48:16
In this lecture session we learn about using kernel methods and also talk about features of using kernel methods in data science with R.
47:43
In this lecture session we learn about documentation and deployment and also talk about features of documentation and deployment in data science with R.
30:09

Course/Topic 10 - Machine Learning (basic to advanced) - all lectures

In this session we will learn about introduction to Machine Learning. We will start by learning about the basics of Linear Algebra required to learn Machine Language. Further we will learn about Linear equations represented by Matrices and Vectors.
32:51
In this module we will learn about the computational roots of matrices. We will learn how to multiply matrix with scalar and vector. We will learn about addition and subtraction of matrices.
27:08
In this module we will learn about Num-Pie Linear Algebra to work on Python. It further includes the understanding of the use of functions - #dot, #vdot, #inner, #matmul, #determinant, #solve, #inv. Basic examples of the #dot, #vdot functions will be discussed.
13:55
In this module we will learn about how the #inner function work in a two-dimension array. We will also learn its usage in #dot and #vdot. We will see explanation of the functions solving examples.
13:39
In this module we will learn about using #matmul function. We will learn about normal product and stack of arrays. We will also learn how to check the dimensions of the array and how to make it compatible.
11:20
In this module we will learn about the #determinant function. The basics of the #determinant function will be explained. Examples will be solved with explanations to understand it.
06:46
In this module we will learn what a Determinant is. We will also learn about how to find a Determinant. We will further learn how to find the Determinant of a 2*2 and 3*3 matrix learn about the basics of #inv function.
08:40
In this module we will learn about the #inv function. We will learn about how to find the inverse of a matrix. We will also learn how to find the Identity matrix for the inverse.
16:32
In this module we will discuss about the inverse of a matrix. We will understand what an Inverse is. We will further learn how the Inverse of a matrix is found.
16:44
In this module we will learn about the difference of the dot( ) and the inner( ). We will see examples of dot( ) and inner( ), We will also learn about the dissimilarities between the dot( ) and inner( ) with the help of examples.
27:37
In this module we will learn about numpy matrix. We will learn the different ways of creating a matrix. We will also learn about a vector as a matrix and its multiplication with matrix.
16:27
In this module we will learn about the #numpy.vdot( ) function. This module is a continuation of the previous module. We will also learn about the #numpy,inner( ) function.
16:24
In this module we will understand the different concepts like Rank, Determinant, Trace, etc, of an array. Then we will learn how to find the item value of a matrix. We will also learn about the matrix and vector products.
25:27
In this module we will learn about the matrix and vector products. We will learn about how it works on imaginary and complex numbers. We will also get an understanding of matmul( ), inner( ), outer( ), linalg.multi_dot( ), tensordot( ), einsom( ), einsum_path( ),linalg.matrix_power( ).
25:02
In this module we will learn about the basics of #inverse of a matrix. We will understand what an Inverse is. We will also see examples of inverse of a matrix and learn how to calculate it.
16:44
In this module we will learn about the basics of Python. We will also learn about the Packages needed by the machine language. We will further learn the basics of numpy, scipy, pandas, skikit-learn, etc. needed machine learning and data science.
16:18
In this module we will understand about SciPy. We will also learn about SkiKit-learn and Theano. We will further learn about TensorFlow, Keras, PyTorch, Pandas, Matplotlib.
19:19
In this module we will see examples of the topics discussed in the previous module. We will also start the basics of Python. We will also solve some basic problems.
18:50
In this module we will continue the basic problems of Python. We will also understand about Operators. We will also see the different operators and its applications.
21:36
In this module we will continue learning the different Operators. We will also learn about Advanced Data types. We will learn and understand the different data types and about Sets.
18:39
In this module we will learn about list. We will see the different functions of list. We will also learn about Jupyter notebook.
17:46
In this module we will learn about #condition statements in Python in brief. We will also learn about the applications of #condition statements We will solve some examples to understand the #condition statements.
25:44
In this module we will learn about the Loop in Pyhton. We will also learn about the different kinds of loops. We will see examples of For loop, and break keyword.
16:48
In this module we will continue with the #for loop. We will also learn about the continue keyword. We will solve examples for the usage of the keywords.
20:48
In this module we will learn about Functions in Python. We will solve examples using different functions. We will understand how functions work.
16:53
In this module we will learn about arguments in functions. We will also solve examples to understand the usage of arguments in functions. We will also learn about #call by reference in Python.
18:40
In this module we will learn about strings. We will also learn about types of arguments for functions in python. We will also see the usage of the different types of arguments.
10:36
In this module we will learn about default arguments. We will also learn about variable arguments. We will solve examples to understand it better.
06:37
In this module we will learn about the remaining arguments. We will understand about default and variable arguments better. We will also learn about keyword arguments.
32:18
In this module we will learn about built-in functions. We will also learn about the different built-in functions in python. We will solve examples to understand the functions better.
37:15
In this module we will continue the previous functions. We will also learn about other built-in functions. We will also learn about bubble sort in python.
09:44
In this module we will learn about the scope of variable in function. We will also learn about the different variables and its usage. We will solve examples using the different variables to understand it better.
13:15
In this module we will learn about the math module in python. We will learn about the different inbuilt functions that deal with math functions. We will solve problems using the different math functions.
12:52
In this module we will continue with the previous lecture. We will also learn about the different arguments in functions. We will also learn about call by reference in python.
18:40
In this module we will continue with the previous lecture. We will also start mathplotlib in python. We will learn the different types of mathplotlib by using jupyter.
1:04:09
In this module we will learn about loan calculator using tkinter. We will also learn how to use the loan calculator. We will solve an example to understand its usage.
33:36
In this module we will continue with the previous lecture. We will learn how to compute payments using functions. We will also learn about the function getmonthlypayment.
36:44
In this module we will learn about numpy function. We will also learn about mathematical and logical operations using numpy. We will also be explained about different numpy arrays.
17:05
In this module we will continue with the previous lecture. We will learn about different numpy attributes. We will solve examples using the different attributes and slicing an array.
24:43
In this module we will learn about advanced slicing of an array. We will use jupyter to do array slicing. We will understand detail how array slicing works.
29:55
In this module we will learn about using jupyter notebook online. We will also learn about ranges. We will learn about creating arrays from ranges. We will also learn about linear space.
28:43
In this module we will learn about the average function. We will also learn about the different averages. We will solve examples to understand the function.
21:25
In this module we will learn about generating random strings and passwords. We will also learn about generating a string of lower and upper case letters. We will solve examples using the different strings.
21:25
In this module we will learn about generating strings. We will also learn about upper case letters and only printing specific letter. We will also learn about alpha numeric letters.
22:46
In this module we will learn about the unique function. We will continue using arrays. We will solve example using unique functions in arrays.
16:52
In this module we will learn about array manipulation function, We will learn about the delete function in numpy. We will solve examples for better understanding.
10:24
In this module we will learn about the insert function in numpy. We will also learn about flattened array. We will solve examples.
10:22
In this module we will learn about examples with two dimension arrays. We will also learn about the ravel function. We will also learn about the rollaxis function, swapaxes function.
14:43
In this module we will learn about statistical functions. We will also learn about min and max values. We will solve examples using the functions.
06:22
In this module we will learn about functions for rounding. We will also learn about round off function, floor function and ceil function. We will solve examples using the functions.
14:16
In this module we will learn about numpy append function. We will also learn about resize function. We will solve examples.
25:20
In this module we will learn about numpy nonzero function. We will also learn about the where function. We will solve examples using the different functions.
14:23
In this module we will learn about matrix library. We will also learn about the different matlib functions We will solve different examples using the matlib function. vvvv
18:25
In this module we will learn about the basic operations that can be done on numpy arrays. We will also learn about arithmetic operations and functions. We will do examples with arithmetic operations.
14:40
In this module we will learn about numpy filter array. We will do programs on numpy filter array. We will solve examples using the filter array.
16:35
In this module we will learn about array manipulation functions. We will see how the array manipulation functions work. We will learn about the different manipulation functions.
29:18
In this module we will learn about broadcasting function in numpy. We will also learn about reshape in numpy. We will also learn about removing function in numpy.
24:23
In this module we will learn about indexing. We will also learn about slicing. We will solve examples to understand the concept.
15:39
In this module we will learn about numpy append function. We will also learn about resize function. We will solve examples using the functions.
25:20
In this module we will learn about conversion of numpy dtypes to native python types. We will also learn to create 4*4 matrix in which 0 and 1 are staggered with zero on the main diagonal. We will also learn to create 10*10 matrix elements on the borders will be equal to 1 and inside 0.
22:11
In this module we will learn how to use a python program to find the maximum and minimum value of a flattened array. We will also see the function called flat and flatten to make the array flattened. We will learn about function import numpy as np and array-np.arrange( )
19:44
In this module we will learn how to generate a random string of a given length. Tutor will address the issues faced in generating random strings. Further in the video, we will discuss the various ways in which generation of a random staring can be performed.
21:46
In this video we will be covering on creating a simple project. We will see the practical on how tutor creates a simple project. We will also see some examples on how to create a simple project. The video talks about how to get common items between 2 python numpy arrays.
21:23
In this video we will talk about another function in python programming called the split function. The function split divides the arrays into sub arrays. The split() method splits a string into an array of substrings. The split() method returns the new array. The split() method does not change the original string. If (" ") is used as separator, the string is split between words.
11:53
This video is a sequel of explanation of spilt function. We will discuss the three types of split functions – 1. Normal split, 2. Horizontal split and 3. Vertical Split. Further we will discuss the roles of split function and what do they do.
12:18
In this video we will learn about the numpy filter array. We will further see what is filtering of array. Getting some elements out of an existing array and creating a new array out of them is called filtering of array, using a bullion index list.
16:35
In this video we will learn about an important topic in Python, i.e Python file handling. We will see what is a file and the type of executable files. Further we will see what is output and how to view the output. Different access modes that can be opened with the file.
14:08
In this video we will see an example on how to open and file in view mode, by giving the name of the file. File statement in Python is used in exception handling to make the code cleaner and much more readable. It simplifies the management of common resources like file streams. ... with open ( 'file_path' , 'w' ) as file : file .
23:38
This video is a continuation of file system tutorial. Here we will see to use the append mode and what is append mode. Python has a built-in open() function to open a file. This function returns a file object, also called a handle, as it is used to read or modify the file accordingly. We can specify the mode while opening a file. In mode, we specify whether we want to read r , write w or append a to the file.
28:56
In this module we will start a new topic known as random module which is a very important part in numpy. Further we will discuss the functionalities of random module to generate random numbers.
14:48
In this module we will see how to generate the arrays on float and hot generate a single floating value from 0 to 1. Further we will see taking array as a parameter and randomly return one of the values.
19:02
In this module we will learn the random module in continuations. The random is the module present in the numpy library. This module contains simple random generation methods.
22:41
In this module how random module contains functions used to generate random numbers. We will also see some permutations and distribution functions.
22:41
In this module we will see the choice functions and the different variants of choice function. Further we will see how to randomly select multiple choices from the list. Random.sample or random.choices are the functions used to select multiple choices or set.
10:03
In this module we will see the difference between the sample function and the choices functions. Further, we will do a random choice from asset with Python, by converting it to tuple.
09:21
In this module we will learn about the random Boolean in Python, using random.choice. In order to generate Random boolean, we use the nextBoolean() method of the java. util. Random class. This returns the next random boolean value from the random generator sequence
43:00
In this module we will learn about the library available in python that is called Pandas. We will see how Pandas is one of the important tools available in Python. Further we will see how Pandas makes sense to list the things.
15:57
In this module we will learn about the basics of Pandas. Further we will see how this an important tool for Data scientist and Analysts and how pandas is the back bone of most of the data projects.
05:53
This module is a sequel of the previous tutorial on Pandas. In this module we will see practical project on pandas using series and dataframes. Lastly we will learn how to handle duplicate and how to handle information method and shape attribute.
32:00
In this video we will see about column clean and how to clean the column. Further we will see how to rename the columns by eliminating symbols and other different ways.
20:58
In this module we will learn about how to work with the missing values or null values. Further we will see if the dataset is inconsistent or has some missing values then how to deal with the missing values when exploring the data.
28:10
In this video we will see how to perform the imputation on column, i.e., metascore which has some null values. Further we will see how to use describe function on the genre column of the dataset.
15:19
In this module we will learn about the frequency of columns. Further we will see about the functio0n called value counts. The value counts function when used on the genre column tells us the frequency of all the columns.
08:09
In this video we will learn about the methods of slicing, selecting and extracting. If these methods are not followed properly then we will receive attribute errors. Further we will learn to manipulate and extract data using column headings and index locations.
18:57
2.7 MATPLOTLIB BASICS
20:22
2.7.1 MATPLOTLIB BASICS
20:38
2.7.2 MATPLOTLIB BASICS
17:32
2.7.3 MATPLOTLIB BASICS
04:00
2.7.4 MATPLOTLIB BASICS
11:31
2.7.5 MATPLOTLIB BASICS
07:23
2.7.6 MATPLOTLIB BASICS
16:55
2.7.7 MATPLOTLIB BASICS
11:53
2.7.8 MATPLOTLIB BASICS
17:16
2.7.9 MATPLOTLIB BASICS
17:40
2.7.9.1 MATPLOTLIB BASICS
16:55
2.7.9.11 MATPLOTLIB BASICS
20:38
2.8 AGE CALCULATOR APP
26:46
2.8.1 AGE CALCULATOR APP
12:22
2.8.2 AGE CALCULATOR APP
33:00
2.8.3 AGE CALCULATOR APP
37:56
3.1 MACHINE LEARNING BASICS
27:27
3.1.1 MACHINE LEARNING BASICS
17:31
3.1.2 MACHINE LEARNING BASICS
17:36
3.1.3 MACHINE LEARNING BASICS
15:38
3.1.4 MACHINE LEARNING BASICS
13:53
3.1.5 MACHINE LEARNING BASICS
11:55
3.1.6 MACHINE LEARNING BASICS
18:51
3.1.7 MACHINE LEARNING BASICS
23:55
3.1.8 MACHINE LEARNING BASICS
22:38
3.1.9 MACHINE LEARNING BASICS
29:13
3.1.9.1 MACHINE LEARNING BASICS
17:36
3.2 MACHINE LEARNING BASICS
08:08
4.1 TYPES OF MACHINE LEARNING
35:11
4.1.1 TYPES OF MACHINE LEARNING
15:03
4.1.2 TYPES OF MACHINE LEARNING
16:18
4.1.3 TYPES OF MACHINE LEARNING
13:58
4.1.4 TYPES OF MACHINE LEARNING
19:45
4.1.5 TYPES OF MACHINE LEARNING
05:12
4.1.6 TYPES OF MACHINE LEARNING
31:39
5.1 TYPES OF MACHINE LEARNING
28:19
5.1.1 TYPES OF MACHINE LEARNING
31:56
5.1.2 TYPES OF MACHINE LEARNING
25:08
5.1.3 TYPES OF MACHINE LEARNING
46:37
5.1.4 TYPES OF MACHINE LEARNING
31:00
5.1.5 TYPES OF MACHINE LEARNING
24:21
5.1.6 TYPES OF MACHINE LEARNING
16:20
5.1.7 TYPES OF MACHINE LEARNING
32:53
5.1.8 TYPES OF MACHINE LEARNING
56:20
5.2 MULTIPLE REGRESSION
34:30
5.2.1 MULTIPLE REGRESSION
37:35
5.2.2 MULTIPLE REGRESSION
40:56
5.2.3 MULTIPLE REGRESSION
56:04
5.2.4 MULTIPLE REGRESSION
46:41
5.2.5 MULTIPLE REGRESSION
38:14
5.2.6 MULTIPLE REGRESSION
37:48
5.2.7 MULTIPLE REGRESSION
1:01:26
5.3 KNN INTRO
26:49
5.3.1 KNN ALGORITHM
48:57
5.3.2 KNN ALGORITHM
11:17
5.3.3 INTRODUCTION TO CONFUSION MATRIX
42:22
5.3.4 INTRODUCTION TO SPLITTING THE DATASET USING TRAINTESTSPLIT
24:37
5.3.5 KNN ALGORITHM
50:29
5.3.6 KNN ALGORITHM
56:10
5.4 INTRODUCTION TO DECISION TREE
44:37
5.4.1 INTRODUCTION TO DECISION TREE
39:32
5.4.2 DECISION TREE ALGORITHM
36:41
5.4.3 DECISION TREE ALGORITHM
20:10
5.4.4 DECISION TREE ALGORITHM
55:37
5.5 UNSUPERVISED LEARNING
23:26
5.5.1 UNSUPERVISED LEARNING
09:16
5.5.2 UNSUPERVISED LEARNING
18:28
5.5.3 UNSUPERVISED LEARNING
29:50
5.5.4 AHC ALGORITHM
46:30
5.5.5 AHC ALGORITHM
19:55
5.6 KMEANS CLUSTERING
23:08
5.6.1 KMEANS CLUSTERING
30:25
5.6.2 KMEANS CLUSTERING
1:01:04
5.6.3 DBSCAN ALGORITHM
37:09
5.6.4 DBSCAN PROGRAM
32:45
5.6.5 DBSCAN PROGRAM
49:56

Course/Topic 11 - Machine Learning with Python - all lectures

In this lecture session we learn about basic introduction to machine learning and also talk about This machine learning process starts with feeding them good quality data and then training the machines by building various machine learning models using the data and different algorithms.
40:25
In this lecture session we learn about types of machine learning in machine learning and also talk about their primary three types of machine learning we also explore and understand the different types of machine learning.
43:26
In this lecture session we learn about Supervised, Unsupervised, and Reinforcement Learning in brief and also talk about some features and factors of Supervised, Unsupervised, and Reinforcement machine Learning.
49:33
In this lecture session we learn about The primary rationale for adopting Python for machine learning is because it is a general purpose programming language that you can use both for research and development and in production. In this post you will discover the Python ecosystem for machine learning.
28:23
In this tutorial we learn about components of python ML Ecosystem in machine learning and also talk about features and factors of Object-Oriented Language: One of the key features of python is Object-Oriented programming. Python supports object-oriented language and concepts of classes, object encapsulation, etc.
38:59
In this tutorial we learn about what pandas is in machine learning and also talk about the pandas package of the most important tool in machine learning and all different tools in brief.
1:01:47
In this lecture session we learn about The most common data format for ML projects is CSV and it comes in various flavors and varying difficulties to parse. In this section, we are going to discuss three common approaches in Python to load CSV data files .
13:13
In this tutorial we learn about regression analysis helps one understand how the typical value of the dependent variable (or 'criterion variable') changes when any one of the independent variables is varied, while the other independent variables are held fixed and also talk about different types of Regression analysis.
38:11
In this tutorial we learn about how Linear regression is used to predict the value of a continuous dependent variable with the help of independent variables. Logistic and also talk about linear regression is both a statistical and a machine learning algorithm. Linear regression is a popular and uncomplicated algorithm used in data science and machine learning.
1:08:44
In this lecture session we learn about the scikit-learn library in machine learning and also talk about what Scikit-Learn is, how it’s used, and what its basic terminology is. While Scikit-learn is just one of several machine learning libraries available in Python, it is one of the best known. The library provides many efficient versions of a diverse number of machine learning algorithms.
33:20
In this lecture session we learn about creating a train and test dataset in machine learning and also talk about The test data set contains data you are going to apply your model to. In contrast, this data doesn’t have any "expected" output. During the test phase of machine learning, this data is used to estimate how well your model has been trained and to estimate model properties.
48:09
In this tutorial we learn about multiple regression is the extension of ordinary least-squares (OLS) regression because it involves more than one explanatory variable. Multiple linear regression (MLR), also known simply as multiple regression, is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.
29:27
In this lecture session we learn about examples of multiple linear regression in machine learning and also talk about features and functions of Linear regression that can only be used when one has two continuous variables—an independent variable and a dependent variable.
56:30
In this tutorial we learn about Polynomial Regression is a regression algorithm that models the relationship between a dependent (y) and independent variable (x) as nth degree polynomial. The Polynomial Regression equation is given below: It is also called the special case of Multiple Linear Regression in ML.
1:01:15
In this lecture session we learn about classification in machine learning as a supervised learning approach and also talk about attempts to learn between a set of variables and a target set of variables of a test.
47:34
In this tutorial we learn about Logistic regression models to help you determine a probability of what type of visitors are likely to accept the offer — or not. As a result, you can make better decisions about promoting your offer or make decisions about the offer itself and also talk about The three types of logistic regression are: Binary logistic regression is the statistical technique used to predict the relationship between the dependent variable (Y) and the independent variable (X), where the dependent variable is binary in nature. For example, the output can be Success/Failure, 0/1 , True/False, or Yes/No.
1:07:05
In this lecture session we learn about what KNN K-nearest neighbors (KNN) is a type of supervised learning algorithm used for both regression and classification. KNN tries to predict the correct class for the test data by calculating the KNN
35:53
In this lecture session we learn about encoding data columns in machine learning Encoding is the process of converting the data or a given sequence of characters, symbols, alphabets etc., into a specified format, for the secured transmission of data. Decoding is the reverse process of encoding which is to extract the information from the converted format. Data Encoding.
41:41
In this tutorial we learn about decision trees in machine learning. Decision tree is the most powerful and popular tool for classification and prediction. A Decision tree is a flowchart like tree structure, where each internal node denotes a test on an attribute, each branch represents an outcome of the test, and each leaf node (terminal node) holds a class label.
44:02
In this lecture session we learn about Support Vector Machine Algorithm. Support Vector Machine (SVM) is a supervised machine learning algorithm used for both classification and regression. Though we say regression problems as well, it's best suited for classification.
35:02
In this lecture session we learn about An Overview of Clustering in the Cloud. Computer clusters, and in particular Kubernetes clusters, have seen a substantial rise in adoption in the last decade. Startups and tech giants alike are leveraging cluster-based architectures to deploy and manage their applications in the cloud.
57:03
In this lecture session we learn about Cluster analysis is an essential human activity. Cluster analysis is used to form groups or clusters of the same records depending on various measures made on these records. The key design is to define the clusters in ways that can be useful for the objective of the analysis.
57:32
In this lecture session we learn about Hierarchical clustering begins by treating every data point as a separate cluster. Then, it repeatedly executes the subsequent steps: Merge the 2 maximum comparable clusters. We need to continue these steps until all the clusters are merged together. In Hierarchical Clustering, the aim is to produce a hierarchical series of nested clusters.
1:01:57
In this tutorial we learn about implementation of Agglomerates hierarchical clusters in machine learning and also talk about features of hierarchical clusters.
45:13
In this tutorial we learn about Association Rule Learning is a rule-based machine learning technique that is used for finding patterns (relations, structures etc.) in datasets. By learning these patterns we will be able to offer some items to our customers.
1:11:02
In this tutorial we learn about Data Mining enables users to analyze, classify and discover correlations among data. One of the crucial tasks of this process is Association Rule Learning. An important part of data mining is anomaly detection, which is a procedure of search for items or events that do not correspond to a familiar pattern.
1:16:49
In this lecture session we learn that Recommender systems are so commonplace now that many of us use them without even knowing it. Because we can't possibly look through all the products or content on a website, a recommendation system plays an important role in helping us have a better user experience, while also exposing us to more inventory we might not discover otherwise.
32:55
In this lecture session we learn about Recommender Function. An important component of any of these systems is the recommender function, which takes information about the user and predicts the rating that user might assign to a product, for example. Predicting user ratings, even before the user has actually provided one, makes recommender systems a powerful tool.
1:00:18
In this lecture session we learn about Collaborative filtering is a difference of memory-based reasoning especially well appropriated to the application of supporting personalized recommendations. A collaborative filtering system begins with a history of personal preferences.
20:44
In this tutorial we learn about implementation of move recommender systems in machine learning and also talk about features and functions of implementation of move recommender systems in brief.
1:17:16

Course/Topic 12 - Deep Learning Foundation - all lectures

In this session we will learn about the introduction to Deep Learning. This video talks about Deep Learning as a series introduction and what is a neural network. Furthermore, we will talk about the 3 reasons to go deep and your choice of Deep net.
52:39
In this video tutorial we will discuss about the neural networks and the 3 reasons to go Deep. Further we will also learn about the use of GPU in artificial intelligence and your choice of deep net.
30:06
In this session we will learn about the deep learning models basics. After this video you will be able to understand the concept of restricted Boltzmann machines and deep belief network. Furthermore, you will learn about the convolution neural network and recurrent neural network.
43:00
In this video course further topics of Deep learning models. After this video you will be able to understand the convolution neural network and its characteristics in detail.
1:26:51
In this video course further topics of Deep learning models. After this video you will be able to understand the recurrent neural network and its characteristics.
15:43
In this session the tutor talks about the basic Additional Deep Learning Models. In this video you will learn about Auto encoders, Recursive neural tensor network and generative adversarial networks
44:28
This session is in continuation to the previous session. In this video we will learn about the Recursive Neural Tensor Network in detail and hierarchical structure of data.
31:44
In this Additional Deep Learning Models tutorial, we will proceed with the Generative Adversarial Networks (GAN) and its uses.
22:22
In this video the tutor explains the Platforms and Libraries of Deep Learning. We will start with what is a deep net platform, H2O.ai and Dato Graph Lab. Further we will see what is a Deep Learning Library and Theano and Caffe. We will also cover a bit of Keras and TensorFlow.
53:43
This tutorial will cover the further part of DatoGraph Lab and its history. Further we wil see the benefits and uses of DatoGraph Lab.
28:19
This tutorial will cover the further part of DatoGraph Lab and its history.
28:15
In this video we will cover the further topics of Deep Learning platform and Libraries such as what is a Deep Learning Library? when and how to use Theano and Caffe as Deep Learning Library.
29:19
In previous video we have leant about Theano and Caffe Deep Learning Library. In this video we will learn about the TensorFlow (free and open source library) as a Deep Learning Library and building Deep Learning Models.
40:18
In this video we will learn about the last type of Library i.e. Keras. Keras is an open source neural network library and runs on top of Theano or TensorFlow. We will further see the advantages of Keras in Deep Learning.
25:34

Course/Topic 13 - CISSP (Cybersecurity) - all lectures

In this lecture session we learn about the basics of cybersecurity and also cover basic functions and factors of cybersecurity in brief.
1:10:40
In this lecture session we learn about CISSP certification guide and also talk about factors of CISSP certification guide in cybersecurity.
33:09
In this lecture session we learn about cyber information systems security professional certification domain and talk about overview of domain in brief.
2:19:49
In this lecture session we learn about CISSP exam preparation guide in cyber security and also talk about more guides for exam preparation.
31:24
In this lecture session we learn about CISSP preparation techniques and also talk about cyber security function and importance.
1:04:33
In this lecture session we learn about risk analysis in cyber information systems security professionals and also talk about risk analysis factors in brief.
54:10
In this lecture session we learn about goals of risk analysis and also talk about risk analysis factors in cybersecurity in brief.
39:20
In this lecture session we learn about cybersecurity goals the object of cybersecurity is to prevent the risk and also cover all types of goals in cyber security.
22:03
In this lecture session we learn about types of cyber attacks in cybersecurity and also talk about how we prevent us from thes cyber attacks.
15:54
In this lecture session we learn about types of cyber attackers in cybersecurity and also cover all attackers in brief.
53:16
In this lecture session we learn about cybersecurity archival storage and also talk about storage factors in brief.
54:48
In this lecture session we learn about cybersecurity VPNS and also talk about other VPNs of cybersecurity and importance of VPNs.
54:04
In this lecture session we learn about cyber security standards in system security professionals and also talk about standard security.
56:36
In this lecture session we learn about cyber security challenges in cyber security in cyber attacks.
1:02:03
In this lecture session we learn about different mail service providers and also talk about mail service providers factors.
1:11:00
In this lecture session we learn about the security and risk management domain and also talk about functions of security and risk management.
59:12
In this lecture session we learn about the importance of security and risk management in brief.
23:10
In this lecture session we learn about factors of security and risk management in brief.
34:05
In this lecture session we learn about implementation of confidentiality and also talk about implementation of integrity in brief.
27:33
In this lecture session we learn boat asset security domain and also talk about functions of asset security domain in brief.
38:12
In this lecture session we learn about asset security domain importance and also talk about more security domains in brief.
1:14:35
In this lecture session we learn about security architecture and engineering domain and also talk about factors of security architecture in brief.
43:22
In this lecture session we learn about the function of security architecture and engineering domain in brief.
26:10
In this lecture session we learn about governance, intelligence and also talk about operation and management.
34:54
In this lecture session we learn about product ciphertext messages and also talk about the importance of security architecture and engineering domain.
22:24
In this lecture session we learn about the fundamentals concept of security models and also talk about more concepts in brief.
26:43
In this lecture session we learn about migration plans and perform migration and also talk about trust and assurance.
12:34
In this lecture session we learn about generating, store and limit the use of cryptography keys.
1:11:38
In this lecture session we learn about fire suppression systems in brief and also talk about fire sprinkler systems in cyber security.
35:09
In this lecture session we learn about certified information system security professionals and also talk about what is cissp.
26:36
In this lecture session we learn about cissp domain and also talk about why we need cissp in cyber security.
33:35
In this lecture session we learn about the importance of cissp in security architecture and engineering.
1:19:30
In this lecture session we learn about communication and network security and also talk about factors of communication and networks security.
18:15
In this lecture session we learn about communication and networks security domain and also talk about functions of network security.
38:59
In this lecture session we learn about deals with networks components related topics like networks models in cyber security.
28:43
In this lecture session we learn about secure network components and also talk about factors of network components.
29:52
In this lecture session we learn about components related topics like networks and also cover more topics in cyber security.
1:37:35
In this lecture session we learn about identity and access management and also cover functions of identity access management.
40:52
In this lecture session we learn about security assessment and testing domain and also talk about other assessments in domain.
10:37
In these lecture sessions we learn about collecting security process data in security assessment in cyber security.
33:23
In these lecture sessions we learn about what is security assessment and testing in brief.
19:24
In these lecture sessions we learn about three general types of vulnerability assessment and also talk about function of vulnerability in brief.
1:32:31
In these lecture sessions we learn about security operation domain in brief and also talk about misuse case testing in brief.
43:36
In this lecture session we learn about security operation in cyber security and also talk about factors of security operation.
31:48
In this lecture session we learn about access control types in security operation in brief and also talk about protective parameters in cyber security.
25:43
In this lecture session we learn about security operation importance and also cover all parameters of security operations.
45:53
In this lecture session we learn about data loss prevention, steganography and watermarking in security operations.
31:31
In this lecture session we learn about training and awareness and also talk about implementing recovery services.
10:35
In this lecture session we learn about a fully functional data center that is always up and running with real time in cyber security.
54:01
In this lecture session we learn about standardizing a configuration across the device in security operation and also talk about system resilient.
2:12:29
In this lecture session we learn about the basics of software development security domain in cyber security and also talk about what is security domain in brief.
53:04
In this lecture session we learn about software development security domain function and importance.
29:18
In this lecture session we learn about software assurance maturity model and also talk about building security in maturity model in brief.
24:16
In this lecture session we learn about unknown vulnerabilities and also talk about software libraries and operating systems.
18:00

Course/Topic 14 - Introduction to DevOps

In this session of you will get an intro about the DevOps.
17:30

Course/Topic 15 - Angular 8 - all lectures

In this session we will learn about the introduction of Angular 8, what is angular and about the pre requisites which are required to learn Angular. Angular is a platform which is used to build dynamic web applications. We will also learn about the challenges faced in modern web framework, such as unified UX, Fluid UX, Progressive web apps and Single page applications.
49:28
In this session we will learn about the Angular CLI Introduction and Angular Directory Structure. Angular CLI helps us to add features to existing Angular applications. Furthermore, in the video we will learn how to install Angular CLI in your machine with practical examples. We will also learn in detail to run your new angular application and sending the data.
34:03
In this session we learn about Angular components and how it is the main building block of Angular application. The main purpose of component is to provide data to the view. We will also learn about important component metadata properties. Furthermore, we will see about different types of component selector.
33:18
In this session we will discuss about data binding and what is data binding in Angular. Data binding is a technique by which data stays in sync between component and view. We will also discuss about the uses of data binding, interpolation in Angular and property binding. Furthermore, we will see practical tutorial of how to run components, interpolation and property binding.
50:56
In this session, we will learn about the class binding in Angular, style binding and event binding. The class binding is used to add or remove classes to and from HTML elements. The video further talks about the three ways by which we can add or remove classes from HTML elements. Furthermore, the video explains how event binding allows us to bind events such as keystrokes, clicks, hover, touché etc. in a method to component.
37:07
In this session we will discuss what are piper is Angular. Pipes are used to display data to the end user and to change appearance of the data. Further we will see the syntax of the different types of pipes in Angular – lower case, upper case, title case, slice, json, percent, number, currency, date.
18:27
In this session we discuss about how to integrate bootstrap with Angular 8. Bootstrap is a CSS framework which helps to develop responsive web pages. We will also learn a number of ways to integrate bootstrap with Angular 8 which are as follows: 1. Including bootstrap CSS and JavaScript in the head section of the index.html file, 2. Importing the bootstrap CSS file in the global styles.css file of your Angular project. 3. Adding the bootstrap CSS and JavaScript files in the styles and script arrays of Angular json.
15:17
In this session we will discuss about Angular Directives and how many types of angular directives are available in Angular. The Angular directives help us to manipulate the Document Objective Model. We will also learn how to change appearance, behavior or layout of a DOM element using directives. We will also see the classification of Angular directives based on their behavior: 1. Component Directives 2. Structural Directives 3. Attribute Directives
54:59
In this session we will discuss in detail about the structural directives in Angular 8. This directive works in conjunction with ngSwitchCase and ngSwitchDefaultDirectives. It is similar to the switch statement of JavaScript.
27:13
In this video we will discuss what is Angular routing and how it is an important key feature for every frontend framework. We will also learn about the process of dividing the UI of an application using URL’s. Further we will also see what is single page application in Angular and server side rendering with Angular Universal, how to work with wild card routes and redirect routes. Lastly, we will one practical example on how to develop such a single page application.
45:05
In this session we will further discuss about Routing specifically on route parameters. We will also learn about the ParaMap Observable and Failed Routes. In this session we will see the last part with respect to the application development.
44:25
In this session we will learn about dependency injection before we go ahead to learn about the services in Angular. Dependencies are services or objects that a class needs to perform its objects or functions. Further, we will see how Angular distinguishes components from services to increase modularity and reusability. Lastly the video will explain about Angular Observable and how it produces multiple values.
47:09
In this session we will learn about template driven forms in Angular. We will learn how Angular uses forms to handle user inputs, though Reactive forms and Template driven forms. Template driven forms are easy to use and similar to Angular JS form and offer two-way data binding with ngModel.
1:05:14
This tutorial is a sequel to the previous video on template driven forms. In this session we will further see about Validation with visual feedback and displaying error messages. We will also learn about Select control validation and Form validation, in a step by step and practical approach.
56:46
This is the last video on template driven forms. In this tutorial we will learn about how to submit form data to the server and how to perform error handling. Further we will also discuss about Express JS and how it is a minimal and flexible NodeJs web application framework. Lastly we will see how to install express in our application using npm install express.
35:09
In this tutorial we will learn what are reactive forms and how to work with reactive forms in Angular. Reactive forms provide direct explicit access to the underlying forms objectives model. We will see the distinguishing of reactive forms and template driven forms and how reactive forms are more robust, scalable, reusable and testable. Lastly we will see how to develop a simple form and a form model.
42:06
This session is in continuation to part 1 of reactive forms. In this session we will highlight the validations. We will learn about 3 types of validations. 1. Simple Validation 2. Custom Validation 3. Cross field Validation We will learn the above by creating a simple registration form and working upon the same.
41:42
In this session we will learn how to apply conditional validation to the form control and how to work with dynamic form controls. Further we will also see how to submit form data. The video will be using a diagram and a registration form to demonstrate the validation.
47:28
In this session we will learn about the component interaction in Angular. Component interaction is when multiple components will interact with each other to share the data between them. Further we will see how our Angular component class will interact with the template and two-way binding script. We will also be covering Setters and Getters in Angular as well as ViewChild ().
29:42
In this session we will be discussing Angular Component Interaction with respect to the component itself. We will learn how components are interacting with each other. We will see the different available components such as parent component and multiple child components. Further we will learn how parent component interacts with child component are interacting with each other and how to send data from parent component to child component. Lastly we will see how to establish the relation between these components.
30:46
In this session we are going to discuss how the interaction is going to happen between parent and child component and how at the same time our parent component can get access to the properties and methods of child component. We will also see how to access properties and methods of child component in the parent class component itself and how to send back data from parent component to child component using Decorator.
40:58
In this session we will be seeing what is Angular CLI and how to install ANGULAR CLI in our machines. Further we will discuss how to generate the angular project using angular CLI and how to work with ng new commands along with options. We will also be seeing the limitation that we will come across and the issues developer will face if they don’t use Angular CLI in real-time projects.
1:06:33
In this session we will see how to generate a component using Angular CLI and how to generate service using Angular CLI. We will also discuss about class and interface with rest to type slip and how to work with ng serve along with options. Lastly we will see how to customize component and other things in Angular CLI.
55:02
In this tutorial we will discuss about component life cycle hooks in Angular. We will see the lifecycle of a component as follows: • Creates the component • Renders the component • Creates and renders the component children • Checks when the component data bound properties change • Destroys the component before removing it from the DOM We will also discuss about the 3 most commonly used hooks.
35:03
In this session we are going to see how to call an external API in Angular by taking the support of http client and the http client module. The tutor will also explain what is API and REST API. API is a set of rules that allows programs to talk to each other. In REST API, rest stands for representational state transfer. Further we will also learn about the HTTP Request Methods.
45:34
In this session we will discuss about how to call external API in Angular with put, patch and delete method. We will further learn how to retrieve data from the server and based on conditions. We will also learn how to update a resource and a particular piece of resource and delete a resource. • PUT: Put method creates a new resource or replaces a representation of the target resources. • PATCH: The patch method is used to apply partial modifications to a resource • DELETE: The delete method deletes the specified resource.
31:23
In this session of Angular we are going to discuss compiling angular application. Further we will see how to use ng command to execute Angular application. We will also see what is ng serve command and when to use ng serve command. The ng serve command helps in building and serving the applications from memory for faster development experience.
27:51
In this session we will discuss about the Angular Development Build and Production build. First we will see how to create an application with commands ng build and ng build production. We will also cover the major differences between ng build development and ng build production. The tutor will then explain source maps and how source maps are used.
37:47
In this session of Angular 8 we will see how to deploy angular 8 applications in Tomcat server. Tomcat is a java based web server and provides an environment to deploy and run web applications. It will also explain the purpose of a server by taking request from a client and processing that request.
39:09
In this tutorial we will discuss about unit testing in angular 8. Further we will see what is unit testing and why we need to use unit testing. Unit testing is nothing but the writing of the test code by the programmer. Further we will see what is Jasmine and some features of Jasmine. In this video, we will also discuss about karma. Lastly, we will write some of the test cases with some sample components in the Angular project.
40:04

Course/Topic 16 - Node.js - all lectures

This tutorial is designed for software programmers who want to learn the basics of Node.js and its architectural concepts. This tutorial will give you enough understanding on all the necessary components of Node.js with suitable examples.
53:21
This video on 'Node.js Installation' will help you in installing Node.js in your system.
13:15
We will talk about the node.js variable scopes, how ECMAScript has defined the variables, and variable hoisting.
16:54
In this session, we'll discuss var, let and const with respect to their scope, use, and hoisting.
18:08
In this session, you’ll learn all about JavaScript’s arrow function syntax — including some of the gotchas you need to be aware of when leveraging arrow functions in your code.
28:32
In this video we’ll learn how to do the same. And also, how to pass arrays to such functions as parameters.
18:32
In this video, Template literals are string literals allowing embedded expressions. You can use multi-line strings and string interpolation features with them.
39:11
There is a special object in JavaScript called module. Exports. When some program includes or import this module (program), this object will be exposed. Therefore, all those functions that need to be exposed or need to be available so that it can used in some other file, defined in module. Exports.
22:55
In this tutorial, we will learn how to construct for loops in JavaScript, consisting of the for, for...of and for...in statements. Loops are an integral part of programming in JavaScript, and are used for automating repetitive tasks and making code more concise and efficient.
25:04
The destructuring assignment syntax is a JavaScript expression that makes it possible to unpack values from arrays, or properties from objects, into distinct variables.The object and array literal expressions provide an easy way to create ad hoc packages of data.
16:21
Node.js global objects are global in nature and they are available in all modules. We do not need to include these objects in our application, rather we can use them directly. These objects are modules, functions, strings and object itself as explained in this video.
17:21
In this section, we will introduce the Node.js module system and its most common usage patterns. Modules are the bricks for structuring non-trivial applications, but also the main mechanism to enforce information hiding by keeping private all the functions and variables that are not explicitly marked to be exported.
24:18
In this tutorial, we are going to do is we want to serve some JSON data using HTTP Module and File System Module. I want to show you when we create a server and how we can actually pull information from an API.
26:57
Node.js has a built-in module called HTTP, which allows Node.js to transfer data over the Hyper Text Transfer Protocol (HTTP).
37:50
In this tutorial, you will learn about the Node.js events module and how it works.
17:45
The Node.js Zlib module which is used to provide compression and decompression (zip and unzip) functionalities. It is implemented using Gzip and deflate/inflate.
10:22
The Path module provides a way of working with directories and file paths.
36:28
Lecture 17 - npm - package.json - installing and uninstalling packages
38:34
Node implements File I/O using simple wrappers around standard POSIX functions. The Node File System (fs) module can be imported using in the tutorial.
53:04
The Node.js Query String provides methods to deal with query string. It can be used to convert query string into JSON object and vice-versa.
41:04
To use query string module, you need to use require('querystring'). The Query String module provides a way of parsing the URL query string.
19:25
This video briefly introduces databases, and how to use them with Node/Express apps. It then goes on to show how we can use Mongoose to provide database access for the Local Library website.
25:11
This tutorial provides a basic understanding of the commonly used operations on Streams. Streams are objects that let you read data from a source or write data to a destination in continuous fashion.
12:00
In Express.js, file upload is slightly difficult because of its asynchronous nature and networking approach.
27:31
This Nodejs tutorial help to send email using nodemailer. You can send mail as a plain text, HTML body and email with attachment.I will demonstrate all flavors of email using node Nodemailer.
17:15
In this session, we’ll give an overview of the criteria to consider when choosing a database, a recommended NoSQL option, and a brief tutorial.
34:50
To create a database in MongoDB, start by creating a MongoClient object, then specify a connection URL with the correct ip address and the name of the database you want to create.
35:38
Node.js can be used in database applications. One of the most popular NoSQL databases is MongoDB.
25:43
In this tutorial, you will learn about the Mostly all modern-day web applications have some sort of data storage system at the backend.
16:51
In this tutorial, we will see how we can use databases from within Node js applications.
19:48
Learn how to access document-based database MongoDB using Node.js in this section.
31:38
MongoDB is a document database with the scalability and flexibility that you want. It is a very popular database used with many web applications. This uplatz video on 'Node.js MongoDB Tutorial' will help you in connecting your web application with a MongoDB database.
17:35
This Uplatz video on Node.js with MongoDB Database Tutorial will help you in connecting your web application with a MongoDB database.
45:22
This video will help you in learning how to connect to a MongoDB database from your Node.js application. In this tutorial, many topics have been covered.
20:38
In this session, we will tell you how you can connect to MongoDB Atlas, a cloud-based DB service, from your local Node.js / Express.js environment.
32:23
In this tutorial, you will learn how to connect to the MySQL database server from a node.js application.
28:06
There are some options to interact with MySQL from a node.js application. In this tutorial, we will show you how to use node.js driver for MySQL called mysqljs/mysql.
43:15
In this tutorial, you have learned how to connect to a MySQL database from a node.js application.
17:57
This Tutorial will help you learn how to connect your webserver to a MySQL database.
26:36
This tutorial will help you understand what is MySql and how to connect Node.js with MySQL along with a nads-on demo. Since it is a very popular combination while working in the web development area, this quick intro is hugely beneficial for people entering into MERN stack, a very popular technology stack used for developing web applications.
24:26
In this tutorial, you will learn how to establish Mysql database connection using Nodejs. This step-by-step guide will help you to install mysql module and sample code, helps you to connect with mysql database.
23:36
In this video you will get to know the basic knowledge of HTML, Javascript and how client-servers work.
40:01
Express is a minimal and flexible Node.js web application framework that provides a robust set of features for web and mobile applications. It is an open-source framework developed and maintained by the Node.js foundation.
44:11
Express provides a minimal interface to build our applications. It provides us the tools that are required to build our app. It is flexible as there are numerous modules available on npm, which can be directly plugged into Express.
36:43
After completing this tutorial, you will be able to build moderately complex websites and back-ends for you mobile applications.
29:22

Course/Topic 17 - ReactJS course - all lectures

In this lecture session we learn about basic introduction of React js and also talk about why we use react js and React js is good for beginners.
33:14
Creating Reusable Component- In this session we learn about how we installation React js in your system and also talk about Node.js webpack and how we create React APP.
15:38
Props; State; Hello World Component; Creating Components; Nesting Components; Component states - Dynamic user-interface; Variations of Stateless Functional Components; setState pitfalls
29:09
In this tutorial we learn about higher order components and how we import components and also talk about features and functions of state components in Reactjs.
30:43
ReactJS component written in TypeScript; Installation and Setup; Stateless React Components in TypeScript; Stateless and property-less Components; Life-cycle methods; Installation of Yarn
39:08
In this tutorial we learn about React js component written in typescript life cycle They serve the same purpose as JavaScript functions, but work in isolation and return HTML. Components come in two types, Class components and Function components, in this tutorial we will concentrate on Function components.
35:14
In this lecture session we learn about The state is a built-in React object that is used to contain data or information about the component. A component's state can change over time; whenever it changes, the component re-renders.
33:06
In this tutorial we learn about The state object is where you store property values that belong to the component. When the state object changes, the component re-renders and also talks about features and factors of the JSX state of things.
35:08
In this lecture session we learn about React ES6 ES6 brings new syntax and new awesome features to make your code more modern and more readable. It allows you to write less code and do more and also talk about features of React ES6 in brief.
38:13
In this lecture session we learn about React class components are rarely used in modern React development but we still need to know them in case we need to work on old legacy projects. If you want to embrace modern React, then you should use function components with hooks.
41:46
In this tutorial we learn about Webpack is a tool that lets you compile JavaScript modules, also known as module bundler. Given a large number of files, it generates a single file (or a few files) that run your app. It can perform many operations: helps you bundle your resources. watches for changes and re-runs the tasks.
30:42
Pure Components- In this lecture session we learn about Parent components passing props down to its children. Children components can not pass props up to their parent component. The Passing of callback functions as a prop allows children components to make changes in their parent component.
41:09
In this lecture session we learn about Controlled components in React are those in which form data is handled by the component's state. Forms are used to store information in a document section. The information from this form is typically sent to a server to perform an action and also talk about basic difference between Controlled vs. Uncontrolled user interaction.
41:27
In this lecture session we learn about Style Libraries. These are tools that assist with applying styles to elements. There are a variety of ways that this can happen. The most common type of style library is a React js processor. These take as input a language similar to React js but with more features, and output standard React js that the browser can understand.
18:57
Fetching Remote Data - Data-Driven- In this lecture session we learn about The most accessible way to fetch data with React is using the Fetch API. The Fetch API is a tool that's built into most modern browsers on the window object ( window. fetch ) and enables us to make HTTP requests very easily using JavaScript promises.
37:09
In this tutorial we learn about React is an open-source front-end JavaScript library maintained by a community of a group of developers and Meta. React is primarily used for building application UI. It is mainly used for developing single-page applications and mobile applications.
29:17
In this tutorial we learn about A "selector function" is any function that accepts the Redux store state (or part of the state) as an argument, and returns data that is based on that state. Selectors don't have to be written using a special library, and it doesn't matter whether you write them as arrow functions or the function keyword.
34:22
In this lecture session we learn about An attribute is a property of an element used to provide access to additional data required for that specific element to process the output.
29:08
In this lecture session we learn about DOM manipulation interacting with the DOM API to change/modify the HTML document that is to be rendered on the web browser. This HTML document can be changed/modified to add elements, remove elements, edit elements, move elements around, etc.
36:25
In this lecture session we learn about The Document Object Model (DOM) is a standard convention for accessing and manipulating elements within HTML and XML documents. Elements in the DOM are organized into a tree-like data structure that can be traversed to navigate, locate, or modify elements and/or content within an XML/HTML document.
19:01
In this lecture session we learn about If you are creating a Deferred, keep a reference to the Deferred so that it can be resolved or rejected at some point. Return only the Promise object via deferred. promise() so other code can register callbacks or inspect the current state.
33:17
In this lecture session we learn about A JavaScript method must be coded to initiate the asynchronous Ajax based file upload; A component must exist on the server to handle the file upload and save the resource locally; The server must send a response to the browser indicating the JavaScript file upload was successful.
23:20
In this lecture session we learn about The React AutoComplete supports the autofill behavior with the help of autofill property. Whenever you change the input value and press the down key, the AutoComplete will autocomplete your data by matching the typed character.
34:09
In this lecture session we learn about React is a popular framework used to make dynamic web apps. It splits HTML into component files using a format called JSX, and uses JavaScript to dynamically render pages. It's very useful, but there's one problem—the loading times are a lot longer than basic pages with no JavaScript. React works by loading a bundle.
51:30
In this tutorial we learn about APIs are used for fetching data from the server and using AJAX and API we call data asynchronously and show it in our HTML. You can make API requests by using browser built- in fetch functions or third party libraries like Axios.
20:45
In this lecture session we learn about Redux Middleware allowing you to intercept every action sent to the reducer so you can make changes to the action or cancel the action. Middleware helps you with logging, error reporting, making asynchronous requests, and a whole lot more.
26:34
In this lecture session we learn about Redux official documentation. It carries a payload of information from your application to store. As discussed earlier, actions are plain JavaScript objects that must have a type attribute to indicate the type of action performed.
28:01
In this lecture session we learn about Environment variables that are embedded into the build, meaning anyone can view them by inspecting your app's files. The environment variables are embedded during the build time. Since Create React App produces a static HTML/CSS/JS bundle, it can't possibly read them at runtime.
36:31
In this tutorial, you will learn about the different questions frequently being asked by any interviewer to the candidates about ReactJS like the difference between Real DOM and Virtual DOM, What is React, what are the limitations of React among many others. With the help of this tutorial, you will be able to clear any interview on ReactJS, giving the most appropriate answers to the questions being asked and will succeed in getting a high paid job in an organization.
33:55

Course/Topic 18 - SQL Programming with MySQL Database - all lectures

In this video get an in-depth introduction to the terminology, concepts, and skills you need to understand database objects, administration, security, and management tools. Plus, explore T-SQL scripts, database queries, and data types
30:09
In this video learn basic of SQL Programming and overview the SQL basic commands and how we use these commands in SQL Programming. This SQL tutorial will teach you basics on how to use SQL in MySQL, SQL Server, MS Access, Oracle, Sybase, Informix, Postgres, and other database systems.
42:45
In this video we talk about DDL (DATA DEFINATION LANGUAGE) and also cover all the basic techniques of DDL.In this video we will learn about the SQL commands – DDL, DML, DCL; SQL Constraints – Keys, Not Null, Check , Default, and also MYSQL Hands-on and basic Querying
33:59
In this video session we learn SQL commands and how to use these commands like select command, insert command, delete command etc. In this video we will learn about hands-on experience on the terminal, creating database, Tables and manipulating data.
38:49
In this video we learn about SQL Basic and Aggregate Functions and also cover different functions of SQL. This tutorial teaches us about clauses and the update command. We will also cover making records, updating and modifying rows.
37:02
In this session we talk about SQL Regular Expression and we also cover all techniques of SQL Regular Expression.This tutorial teaches us about clauses and the update command. We will also cover making records, updating and modifying rows and EML commands.
36:07
In this video we learn about SQL Comparison Clauses and how we use Comparison Clauses in SQL. This tutorial covers Comparison Operators by relating values by a mathematical symbol which is used to compare two values. Learn about comparison operators result - TRUE, FALSE, or UNKNOWN
28:30
In this session we learn about SQL String and also cover all types of string in SQL and how we can use SQL Strings. In this video we will learn about the basic string functions such as concat_ws, file format, and insert function, L-case, u case, and lower case. We will also learn about basic functions such as upper functions.
30:31
In this session we cover advance level string function and also cover all different commands we use in SQL String Function. This video is a sequel for string functions tutorial. In this tutorial we will learn few most useful string functions such as spaces and null issue as well, L-Pad command.
38:20
In this SQL String function part 3 we learn select Repeat function and Select Replace function and also cover different between Select Repeat function and Select Replace function. This tutorial is another sequel to string functions, however, these functions are used less and not used that frequently. We will further learn here about the repeat function, absolute function, ceiling, and floor and down functions.
23:20
In this session we learn about SQL Numeric Functions and how we use Numeric functions in SQL. In this video, we will be covering numerical functions. Learn about the basic date functions and also about truncate functions.
36:50
In this video session we learn about SQL Numeric Function and also cover the basic functionality of SQL Numeric Function. SQL Data Functions. In this video we will learn about few more Date functions. We will further look into the day function option as well. This tutorial covers basic querying over a single table.
46:38
: In this video we talk about SQL Joins Introduction and Demonstration and basic join’s function and how to make table using joins. In this tutorial learn about joints in SQL. This tutorial teaches us how to connect two different tables with joints. We will also cover the topic of querying two or more tables and about subquery .
36:52
In this lecture last session we talk about MySQL Workbench and procedures and Views and MySQL Workbench functionality. In this tutorial learn about SQL in automating things. This tutorial covers stroll procedure, functions and views which are helpful for automation purposes in SQL.
21:22

Course/Topic 19 - Unix and Shell Scripting course - all lectures

Linux tutorial provides basic and advanced concepts of Linux. Our Linux tutorial is designed for beginners and professionals. Linux is an open-source operating system. It is like Windows, Mac, Android, etc. Unix is also an operating system like Linux.
42:35
This tutorial grounds you in the basic Linux commands for manipulating files and directories. Learn about, List directory contents, Copy, move, or remove files and directories, manipulate multiple files and directories recursively, use wildcard patterns for manipulating files, Use the find command to locate and act on files based on type, size, or time.
24:31
This Tutorial is all about using a UNIX and Linux command for listing directory contents. Examples of listing a directory, showing hidden files, showing long listings, sorting on various items and showing recursive listings.
28:39
In this session you will learn about the Unix operating system which is capable of editing command lines saved in the history file. Commands in the file can be recalled and executed but, if that command was wrong or needs to be changed then the command line editor can be used.
26:56
This tutorial helps people to understand some of the basics of shell script programming (aka shell scripting), and hopefully to introduce some of the possibilities of simple but powerful programming available under the Bourne shell. As such, it helps you as a basis for one-on-one or group tutorials and exercises, and as a reference for subsequent use.
22:52
This Shell Scripting tutorial helps to learn a basic understanding of the Linux/Unix shell scripting program to advanced concepts of Shell Scripting. This Shell Script tutorial designed for beginners and professionals who want to learn What is Shell Scripting? How shell scripting works, types of shell, and more.
19:57

Course/Topic 20 - Google Analytics - all lectures

Lecture 1 - Introduction to Google Analytics
02:06
Lecture 2 - Setting up Google Analytics using GTM
04:56
Lecture 3 - Account-Property-View
14:04
Lecture 4 - Google Analytics Home
12:55
Lecture 5 - Real-time Report
07:09
Lecture 6 - Audience Report and Segments - part 1
15:47
Lecture 7 - Audience Report and Segments - part 2
13:02
Lecture 8 - Acquisition Report - part 1
11:35
Lecture 9 - Acquisition Report - part 2
17:13
Lecture 10 - Behavior Report - part 1
19:44
Lecture 11 - Behavior Report - part 2
17:04
Lecture 12 - Conversions Report
12:42
Lecture 13 - Customization and Discover
07:22

Course/Topic 21 - Microsoft Excel - all lectures

Lecture 1 - Introduction to Microsoft Excel
19:48
Lecture 2 - Key in Data
12:46
Lecture 3 - Font and Alignment
13:52
Lecture 4 - Cut Paste and Format Painter
07:20
Lecture 5 - Control plus Keys
23:40
Lecture 6 - Home Commands and Clipboard
20:09
Lecture 7 - File Tab
12:49
Lecture 8 - Sorting and Filtering
26:09
Lecture 9.1 - Basic Formulas
23:00
Lecture 9.2 - Text Formulas
32:49
Lecture 10.1 - VLookup - part 1
26:39
Lecture 10.2 - VLookup - part 2
06:20
Lecture 10.3 - HLookup
14:22
Lecture 10.4 - This is a bonus session on Vlookup from a different tutor
10:27
Lecture 10.5 - This is a bonus session on Vlookup from a different tutor
05:02
Lecture 11.1 - Pivot Tables - part 1
15:16
Lecture 11.2 - Pivot Tables - part 2
07:14
Lecture 11.3 - Pivot Tables - part 3
23:38
Lecture 11.4 - Pivot Tables - part 4
11:47
Lecture 12.1 - Charts - part 1
09:05
Lecture 12.2 - Charts - part 2
21:01
Lecture 12.3 - Column Charts
30:28
Lecture 12.4 - Bar Charts
09:07
Lecture 12.5 - Line Charts
09:57

Course/Topic 22 - Google Sheets course - all lectures

Lesson 1 - Introduction to Google Sheets
02:31
Lesson 2 - Menu Options - File
08:40
Lesson 3 - Menu Options - Edit
03:30
Lesson 4 - Menu Options - View
04:49
Lesson 5 - Menu Options - Insert
04:59
Lesson 6 - Menu Options - Format
10:21
Lesson 7 - Menu Options - Data and more
18:17
Lesson 8 - Entering Data and Editing
07:12
Lesson 9 - Functions - Numeric Function
15:24
Lesson 10 - Functions - Text Function
30:38
Lesson 11 - Functions - Date Functions
06:21
Lesson 12 - Charts and Conditional Formatting
22:12
Lesson 13 - Pivot Tables
23:21
Lesson 14 - Saving - Sharing
06:22

Course/Topic 23 - Project Management Fundamentals - all lectures

In this first video tutorial on Project Management, you will learn an Introduction to Project Management, its history, benefits, an illustration to Gantt Chart, a view on some of the International standards of practicing Project Management, an overview of what exactly is a project, its relationship with General Project Management practices, Triple Constraints Theory and the role of a Project Manager and its characteristics in Project Management.
39:36
In this second session of Project Management, you will understand what is Process Oriented Project Management, Project Processes and its categories, what is Project Management and Product Oriented processes and an overview of different process groups and its knowledge areas.
21:23
In this lecture, you will learn what is a process in Project Management and its different stages in a Project Life cycle, how a process is linked to different process groups. Also, you will learn about the different Knowledge Areas related to a Process in Project Management.
28:19
In this video, you will learn about the Project Planning Process and Group Processes and the different processes involved in managing the Scope and Scheduled Constraints.
26:25
In this last session on Project Management Fundamentals, you will learn about the different constraints involved like Cost, Quality, Resources, Risks, etc. in a Process Group and how it helps in managing the entire project in Project Management.
20:36

Course/Topic 24 - Microsoft Project (basic to advanced) - all lectures

Lecture 1 - Overview of Microsoft Project
07:47
Lecture 2 - The Stage
24:17
Lecture 3 - The Back Stage
17:29
Lecture 4 - Views and Tables in MSP
24:03
Lecture 5 - Project Initiation - part 1
27:44
Lecture 6 - Project Initiation - part 2
07:16
Lecture 7 - Tasks and Milestones
24:00
Lecture 8 - Linking Tasks
28:24
Lecture 9 - More on Linking Tasks
29:41
Lecture 10 - Creating Resources
29:04
Lecture 11 - Creating Resources - advanced
23:25
Lecture 12 - Assigning Resources
27:58
Lecture 13 - Applying Cost Tables
11:42
Lecture 14 - Units Work Duration
34:39
Lecture 15 - Handy Features - revised
09:36
Lecture 16 - Critical Path Identification
15:58
Lecture 17 - Resource Leveling
21:15
Lecture 18 - Baselining
16:02
Lecture 19 - Updating Project - part 1
25:48
Lecture 20 - Updating Project - part 2
17:44
Lecture 21 - Updating Project - part 3
23:29
Lecture 22 - Monitoring
28:24
Lecture 23 - Controlling - part 1
22:52
Lecture 24 - Controlling - part 2
19:54
Lecture 25 - Reports Pack
32:56
Lecture 26 - Support EVM
11:58

Course/Topic 25 - Leadership and Management - all lectures

In this lecture session we learn about honesty and integrity in leadership and management and also talk about some basic terms of leadership and management.
23:44
In this lecture session we learn about how confidence is a must in leadership and management and also talk about the importance of confidence in leadership and management.
34:07
In this tutorial we learn about A soft skill is a personal attribute that supports situational awareness and enhances an individual's ability to get a job done. The term soft skills is often used as a synonym for people skills or emotional intelligence.
20:31
In this lecture session we learn about Soft skills, also called people skills, are the mix of social and interpersonal skills, character traits, and professional attitudes that all jobs require. Teamwork, patience, time management, communication, are just a few examples.
22:58
In this lecture session we learn that Communication in teams is more than just efficient work. It allows everyone on the team to be educated on any topic that may affect their work. Moreover, it develops trust, builds camaraderie among the team members, boosts morale, and helps employees stay engaged in the workplace.
26:44
In this lecture session we learn about Effective communication can help to foster a good working relationship between you and your staff, which can in turn improve morale and efficiency.
29:21
In this lecture session we learn about what commitment Concentration – leadership commitment involves making a personal decision to support the change no matter what. It is incongruous to ask for change in others while failing to exhibit the same level of commitment. Concentration requires maintaining focus throughout the change not just at the beginning.
15:12
In this lecture session we learn about Market leadership is the position of a company with the largest market share or highest profitability margin in a given market for goods and services. Market share may be measured by either the volume of goods sold or the value of those goods.
36:11
In this lecture session we learn that Motivational leadership is defined by positivity and vision. Motivational leaders make decisions, set clear goals and provide their teams with the empowerment and tools to achieve success. Motivational leaders evoke and see the best in their employees, inspiring them to work toward a common goal.
30:53
In this lecture session we learn about A primary task of leadership is to direct attention. To do so, leaders must learn to focus their own attention. When we speak about being focused, we commonly mean thinking about one thing while filtering out distractions.
28:19
In this tutorial we learn about Marketing analytics helps collect and strengthen data from across all marketing channels. This information is key to improving marketing efforts and driving them forward to achieve business goals.
37:05
In this lecture session we learn about Marketing automation is the integration of data and processes from other sales and marketing channels into an organized central platform. A comprehensive marketing automation hub complements and organizes the customer journey. It integrates all of a business's channels and outreach within the customer database.
32:03
In this tutorial we learn about Growth hacking (also known as 'growth marketing') is the use of resource-light and cost-effective digital marketing tactics to help grow and retain an active user base, sell products and gain exposure.
31:59
In this tutorial we learn about Growth Hacking is a new field focusing solely on growth, based on a data-driven, experiment-based process. A growth hacker explores new growth opportunities systematically in any part of the customer journey, from awareness through marketing to brand ambassadors by optimizing the product.
27:50
In this lecture session we learn about Product marketing is the process of bringing a product to market. This includes deciding the product's positioning and messaging, launching the product, and ensuring salespeople and customers understand it. Product marketing aims to drive the demand and usage of the product.
30:51
In this lecture session we learn about the marketing, sales, product, and customer success teams are no longer siloed. They are interwoven in a cohesive experience with the product at the center, and the customer at the center of the product.
27:38
In this tutorial we learn about how Product marketers know the message and story to convey, who to convey it to, and at what time it needs conveying- but marketing is responsible for turning that knowledge into blog posts, ad copy, and press releases.
18:16
In this lecture session we learn about PR involves communicating with your market to raise awareness of your business, build and manage your business's reputation and cultivate relationships with consumers. While marketing focuses on promoting actual products and services, public relations focuses on promoting awareness, attitudes and behavior change.
34:17
In this lecture session we learn about building relationships with the public in order to create a positive public image for a company or organization. It also has different disciplines, such as corporate communications, internal communications, marketing communications, crisis communications.
37:40
In this lecture session we learn about Public relations helps build an online presence across multiple platforms – social media, earned media, paid media and more. Public relations is important because it involves storytelling. Advertising and marketing can only go so far, and can become bothersome at times, turning consumers away from the product.
33:06
In this lecture session we learn about Both advertising and PR help build brands and communicate with target audiences. The most basic difference between them is that advertising space is paid while public relations results are earned through providing the media with information in the form of press releases and pitches
17:49

Course Objectives Back to Top

•How to onboard into new organizations

•How to implemented Agile correctly

•How to create a robust build process

•How to perform a rigorous fire drill to test your team

•How to risk-assessment to identify pending failures

•How to analyze the sprint backlog for common mistakes

Course Syllabus Back to Top

Certification Back to Top

There are several certifications in various technology domains that can enhance a CTO's knowledge and credibility in their field. These certifications can be valuable for CTOs to demonstrate expertise in specific areas and stay updated with the latest industry trends. Some relevant certifications include:

1. Certified Information Systems Security Professional (CISSP): This certification is ideal for CTOs who want to demonstrate expertise in cybersecurity and information security management.

2. Project Management Professional (PMP): While not directly related to CTO roles, the PMP certification can be valuable for CTOs who lead technology projects and teams, as it demonstrates project management skills.

3. ITIL (Information Technology Infrastructure Library) Certifications: ITIL certifications are relevant for CTOs involved in IT service management and aligning IT services with business needs.

4. Certified Scrum Master (CSM) or Certified Scrum Professional (CSP): For CTOs working in agile development environments, these certifications can be beneficial.

5. Certified Data Professional (CDP): Relevant for CTOs dealing extensively with data management, data governance, and analytics.

6. Cloud Certifications (e.g., AWS Certified Solutions Architect, Microsoft Azure Certifications): For CTOs focusing on cloud infrastructure and solutions.

7. Certified Blockchain Professional: For CTOs exploring blockchain technology applications in their organizations.

It's essential to note that while certifications can add value, they should be considered as a complement to the CTO's experience and skills, not a replacement. The CTO's success relies heavily on their ability to align technology with business strategy, lead technology teams, and drive innovation, which often comes from years of practical experience in various technology roles.

Since the technology landscape is continually evolving, CTOs should stay updated with industry trends, attend relevant conferences and seminars, and participate in professional development activities to enhance their knowledge and skills. Additionally, networking with other technology leaders and sharing experiences can also contribute significantly to a CTO's growth and success.

Career & Jobs Back to Top

The career path and job scope of a Chief Technology Officer (CTO) can vary depending on the size and nature of the organization. Generally, the CTO is a high-level executive responsible for overseeing all aspects of an organization's technology strategy, infrastructure, and operations.

Career Path

1. Technology Specialist/Engineer: The career path often begins with roles such as software engineer, system administrator, network specialist, or other technology-focused positions. This phase allows individuals to gain hands-on experience and technical expertise in specific areas.

2. Technology Manager/Team Lead: As their experience grows, professionals may progress to managerial roles, leading technology teams responsible for specific functions like software development, infrastructure management, or cybersecurity.

3. Director/Head of Technology: Advancing further, individuals may take on larger leadership roles, overseeing multiple technology teams and setting technology strategies aligned with business objectives.

4. Vice President of Technology/Chief Information Officer (CIO): Some professionals may move to senior leadership roles, like Vice President of Technology or CIO, where they have a broader responsibility for technology across the organization.

5. Chief Technology Officer (CTO): Finally, after gaining extensive experience and proven leadership in technology strategy and execution, individuals may be appointed as CTO, the highest-ranking technology executive in the organization.

Job Scope of a CTO

1. Technology Strategy: Developing and executing a comprehensive technology strategy that aligns with the organization's overall business objectives and goals.

2. Innovation and Research: Staying up-to-date with emerging technologies and industry trends, and identifying opportunities for technology innovation to gain a competitive edge.

3. Technology Infrastructure: Overseeing the design, implementation, and maintenance of the organization's technology infrastructure, including networks, hardware, and software.

4. Cybersecurity and Data Privacy: Ensuring the organization's technology assets are protected from cyber threats and that data privacy regulations are adhered to.

5. Team Leadership and Development: Building and leading a skilled and motivated technology team, providing mentorship, training, and opportunities for professional growth.

6. Vendor Management: Evaluating and managing relationships with technology vendors, ensuring that they provide reliable products and services.

7. Budgeting and Resource Allocation: Developing and managing the technology budget, optimizing technology spending, and allocating resources efficiently.

8. Technology Governance: Implementing and enforcing technology governance frameworks and best practices to ensure compliance and risk management.

9. Business Continuity and Disaster Recovery: Developing and testing plans to ensure technology systems can quickly recover in the event of a disaster or disruption.

10. Collaboration with Other Executives: Collaborating with other C-suite executives, especially the CEO and CFO, to ensure technology supports the organization's overall business strategy.

11. Technology Partnerships and Alliances: Exploring and forming partnerships with technology companies to leverage their expertise and accelerate innovation.

12. Intellectual Property Management: Protecting the organization's intellectual property and ensuring that technology-related patents and innovations are appropriately managed.

Overall, the CTO plays a crucial role in driving technology initiatives that support the organization's growth and success. They combine technical expertise with strategic vision and leadership skills to make informed decisions that drive innovation, efficiency, and competitiveness.

Interview Questions Back to Top

Below are commonly asked interview questions along with sample answers for a Chief Technology Officer (CTO) interview:

1. Can you describe your experience as a Chief Technology Officer and the key achievements you have had in previous roles?

As a CTO, I have led technology teams, implemented innovative solutions, and optimized technology infrastructure. At Company A, I spearheaded the development of a new product that significantly increased revenue.

2. How do you approach aligning technology strategy with business goals as a CTO?

Aligning technology strategy with business goals involves understanding the organization's objectives and identifying technology solutions that support those goals.

3. How do you stay updated with the latest advancements in technology and industry trends?

I actively participate in technology forums, attend conferences, and encourage continuous learning within the technology team.

4. Can you share an example of a challenging technology project you led as a CTO?

How did you approach it? During a complex system migration, I organized a cross-functional team, set clear milestones, and communicated regularly to ensure a smooth transition.

5. How do you approach technology risk management and ensuring data security as a CTO?

Technology risk management involves conducting risk assessments, implementing security protocols, and staying updated with cybersecurity best practices.

6. Can you discuss your experience in managing technology budgets and optimizing technology spending?

Managing technology budgets requires prioritizing investments in technology that align with business needs and deliver a strong return on investment (ROI).

7. How do you approach technology infrastructure management and ensuring system reliability and performance?

Technology infrastructure management involves proactive monitoring, capacity planning, and implementing redundancy to ensure optimal system performance.

8. Can you share an example of a situation where you successfully led a team through a major technology upgrade or implementation?

During an enterprise-wide software upgrade, I facilitated extensive training for employees and collaborated with vendors to ensure a seamless transition.

9. How do you approach technology governance and ensuring compliance with industry regulations and data protection laws?

Technology governance involves setting policies, procedures, and controls to ensure compliance with regulations and data protection laws.

10. Can you discuss your experience in managing technology vendor relationships and vendor selection processes?

Managing technology vendor relationships involves clear communication, performance monitoring, and negotiating favorable contracts.

11. How do you approach technology project prioritization and resource allocation?

Technology project prioritization involves evaluating projects based on strategic importance, resource availability, and potential impact on business objectives.

12. Can you share an example of a situation where you successfully implemented technology initiatives to enhance employee productivity?

By introducing collaboration tools and streamlining workflows, we improved employee productivity and reduced manual processes.

13. How do you approach technology service management and ensuring prompt resolution of technology incidents?

Technology service management involves implementing ITIL best practices and using ticketing systems to track and resolve incidents efficiently.

14. Can you discuss your experience in managing technology compliance audits and ensuring the organization meets regulatory requirements?

Managing technology compliance audits involves preparing documentation, addressing audit findings, and continuously improving compliance processes.

15. How do you approach technology disaster recovery planning and ensuring business continuity?

Technology disaster recovery planning involves developing recovery strategies, conducting regular testing, and ensuring backups are secure and up-to-date.

16. Can you share an example of a situation where you successfully led a data migration project to a new platform?

During a data migration project, I collaborated with cross-functional teams, conducted data mapping, and performed rigorous testing to ensure data accuracy.

17. How do you approach technology talent development and fostering a culture of innovation within the technology department?

Technology talent development involves providing training opportunities, encouraging certifications, and promoting a culture of continuous learning.

18. Can you discuss your experience in implementing technology governance frameworks, such as COBIT or ITIL?

Implementing technology governance frameworks involves aligning technology processes with business goals and establishing clear accountability and responsibilities.

19. How do you approach technology asset management and optimizing the use of technology resources?

Technology asset management involves tracking hardware and software assets, optimizing licenses, and identifying opportunities for cost savings.

20. Can you share an example of a situation where you successfully led a technology adoption initiative to improve business processes?

By introducing robotic process automation (RPA), we automated manual tasks, resulting in increased efficiency and reduced operational costs.

21. How do you approach technology vendor risk management and ensuring vendors meet security and compliance requirements?

Technology vendor risk management involves conducting vendor assessments and due diligence to ensure vendors meet security and compliance standards.

22. Can you discuss your experience in managing technology projects with geographically dispersed teams?

Managing geographically dispersed teams requires effective communication, collaboration tools, and establishing clear project milestones.

23. How do you approach technology innovation and identifying opportunities for technology-driven business improvements?

Technology innovation involves staying informed about emerging technologies, conducting pilot projects, and seeking input from key stakeholders.

24. Can you share an example of a situation where you successfully led a cloud migration project to improve scalability and flexibility?

During a cloud migration, we optimized workloads and implemented cloud security measures, resulting in enhanced scalability and cost efficiency.

25. How do you approach technology compliance and ensuring adherence to industry standards and regulatory requirements?

Technology compliance involves regular audits, implementing controls, and collaborating with legal and compliance teams.

26. Can you discuss your experience in managing technology projects with tight deadlines and high pressure?

Managing projects under pressure requires setting realistic expectations, fostering a sense of urgency, and maintaining open communication with stakeholders.

27. How do you approach technology innovation and fostering a culture of experimentation within the technology department?

Technology innovation involves encouraging creativity, rewarding innovative ideas, and providing the necessary resources for experimentation.

28. Can you share an example of a situation where you successfully led a technology project that resulted in cost savings for the organization?

By virtualizing server infrastructure and optimizing hardware utilization, we achieved significant cost savings on data center operations.

29. How do you approach technology change management and ensuring smooth transitions during technology implementations?

Technology change management involves engaging stakeholders, communicating the benefits of the change, and providing training and support during transitions.

30. Can you discuss your experience in managing technology teams during periods of rapid growth or organizational change?

During periods of growth or change, I ensure that the technology team is agile, adaptable, and equipped to support the evolving needs of the organization.

31. How do you approach technology capacity planning and scaling technology resources to accommodate business growth?

Technology capacity planning involves analyzing historical data, projecting future needs, and aligning technology resources with business demands.

32. Can you share an example of a situation where you successfully implemented technology initiatives to enhance customer experience?

By integrating customer data across touchpoints, we personalized customer interactions and improved overall satisfaction.

33. How do you approach technology budget forecasting and ensuring financial transparency in technology spending?

Technology budget forecasting involves collaborating with finance teams, tracking expenses, and providing detailed budget reports.

34. Can you discuss your experience in managing technology projects with cross-functional teams and ensuring effective collaboration?

Managing cross-functional teams requires strong communication, fostering a collaborative culture, and addressing any conflicts promptly.

35. Can you share an example of a situation where you successfully led a technology project to enhance cybersecurity measures and protect against cyber threats?

By implementing multi-factor authentication and conducting employee cybersecurity training, we significantly reduced the risk of data breaches.

36. How do you approach technology innovation and creating a culture of continuous improvement within the technology department?

Technology innovation involves encouraging new ideas, providing resources for research and development, and recognizing innovative contributions.

37. Can you discuss your experience in managing technology projects with limited resources or tight budgets?

Managing projects with limited resources requires effective resource allocation, prioritization, and finding creative solutions to deliver results.

38. How do you approach technology knowledge management and ensuring effective knowledge transfer within the technology department?

Technology knowledge management involves documenting best practices, conducting knowledge-sharing sessions, and establishing a knowledge repository.

39. Can you share an example of a situation where you successfully led a technology project to improve data analytics capabilities?

By implementing a data analytics platform and training team members, we improved data-driven decision-making and business insights.

40. How do you approach technology workforce planning and addressing skill gaps within the technology department?

Technology workforce planning involves conducting skills assessments, providing training opportunities, and recruiting talent with specialized expertise.

41. Can you discuss your experience in managing technology projects with external partners or vendors?

Collaborating with external partners requires clear communication, defining project expectations, and establishing mutual accountability.

42. How do you approach technology project post-mortems and using lessons learned to improve future project execution?

Technology project post-mortems involve analyzing project outcomes, identifying strengths and weaknesses, and implementing improvements for future projects.

43. Can you share an example of a situation where you successfully led a technology project to enhance data integration and data accessibility?

By implementing a data integration platform, we streamlined data workflows and empowered teams to access critical data in real-time.

44. How do you approach technology budget forecasting and ensuring financial transparency in technology spending?

Technology budget forecasting involves collaborating with finance teams, tracking expenses, and providing detailed budget reports.

45. Can you discuss your experience in managing technology projects with cross-functional teams and ensuring effective collaboration?

Managing cross-functional teams requires strong communication, fostering a collaborative culture, and addressing any conflicts promptly.

46. Can you share an example of a situation where you successfully led a technology project to enhance cybersecurity measures and protect against cyber threats?

By implementing multi-factor authentication and conducting employee cybersecurity training, we significantly reduced the risk of data breaches.

47. How do you approach technology innovation and creating a culture of continuous improvement within the technology department?

Technology innovation involves encouraging new ideas, providing resources for research and development, and recognizing innovative contributions.

48. Can you discuss your experience in managing technology projects with limited resources or tight budgets?

Managing projects with limited resources requires effective resource allocation, prioritization, and finding creative solutions to deliver results.

49. How do you approach technology knowledge management and ensuring effective knowledge transfer within the technology department?

Technology knowledge management involves documenting best practices, conducting knowledge-sharing sessions, and establishing a knowledge repository.

50. Can you share an example of a situation where you successfully led a technology project to improve data analytics capabilities?

By implementing a data analytics platform and training team members, we improved data-driven decision-making and business insights.

Note: The provided responses are sample answers and should be tailored to the individual's specific experiences and accomplishments. Additionally, in a real interview, candidates are encouraged to be concise, confident, and provide concrete examples to support their responses.

Course Quiz Back to Top

Start Quiz

FAQs Back to Top

Q1. What are the payment options?
A1. We have multiple payment options: 1) Book your course on our webiste by clicking on Buy this course button on top right of this course page 2) Pay via Invoice using any credit or debit card 3) Pay to our UK or India bank account 4) If your HR or employer is making the payment, then we can send them an invoice to pay.

Q2. Will I get certificate?
A2. Yes, you will receive course completion certificate from Uplatz confirming that you have completed this course with Uplatz. Once you complete your learning please submit this for to request for your certificate https://training.uplatz.com/certificate-request.php

Q3. How long is the course access?
A3. All our video courses comes with lifetime access. Once you purchase a video course with Uplatz you have lifetime access to the course i.e. forever. You can access your course any time via our website and/or mobile app and learn at your own convenience.

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Q5. Do you take exam? Do I need to pass exam? How to book exam?
A5. We do not take exam as part of the our training programs whether it is video course or live online class. These courses are professional courses and are offered to upskill and move on in the career ladder. However if there is an associated exam to the subject you are learning with us then you need to contact the relevant examination authority for booking your exam.

Q6. Can I get study material with the course?
A6. The study material might or might not be available for this course. Please note that though we strive to provide you the best materials but we cannot guarantee the exact study material that is mentioned anywhere within the lecture videos. Please submit study material request using the form https://training.uplatz.com/study-material-request.php

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Q8. Do you provide any discounts?
A8. We run promotions and discounts from time to time, we suggest you to register on our website so you can receive our emails related to promotions and offers.

Q9. What are overview courses?
A9. Overview courses are 1-2 hours short to help you decide if you want to go for the full course on that particular subject. Uplatz overview courses are either free or minimally charged such as GBP 1 / USD 2 / EUR 2 / INR 100

Q10. What are individual courses?
A10. Individual courses are simply our video courses available on Uplatz website and app across more than 300 technologies. Each course varies in duration from 5 hours uptop 150 hours. Check all our courses here https://training.uplatz.com/online-it-courses.php?search=individual

Q11. What are bundle courses?
A11. Bundle courses offered by Uplatz are combo of 2 or more video courses. We have Bundle up the similar technologies together in Bundles so offer you better value in pricing and give you an enhaced learning experience. Check all Bundle courses here https://training.uplatz.com/online-it-courses.php?search=bundle

Q12. What are Career Path programs?
A12. Career Path programs are our comprehensive learning package of video course. These are combined in a way by keeping in mind the career you would like to aim after doing career path program. Career path programs ranges from 100 hours to 600 hours and covers wide variety of courses for you to become an expert on those technologies. Check all Career Path Programs here https://training.uplatz.com/online-it-courses.php?career_path_courses=done

Q13. What are Learning Path programs?
A13. Learning Path programs are dedicated courses designed by SAP professionals to start and enhance their career in an SAP domain. It covers from basic to advance level of all courses across each business function. These programs are available across SAP finance, SAP Logistics, SAP HR, SAP succcessfactors, SAP Technical, SAP Sales, SAP S/4HANA and many more Check all Learning path here https://training.uplatz.com/online-it-courses.php?learning_path_courses=done

Q14. What are Premium Career tracks?
A14. Premium Career tracks are programs consisting of video courses that lead to skills required by C-suite executives such as CEO, CTO, CFO, and so on. These programs will help you gain knowledge and acumen to become a senior management executive.

Q15. How unlimited subscription works?
A15. Uplatz offers 2 types of unlimited subscription, Monthly and Yearly. Our monthly subscription give you unlimited access to our more than 300 video courses with 6000 hours of learning content. The plan renews each month. Minimum committment is for 1 year, you can cancel anytime after 1 year of enrolment. Our yearly subscription gives you unlimited access to our more than 300 video courses with 6000 hours of learning content. The plan renews every year. Minimum committment is for 1 year, you can cancel the plan anytime after 1 year. Check our monthly and yearly subscription here https://training.uplatz.com/online-it-courses.php?search=subscription

Q16. Do you provide software access with video course?
A16. Software access can be purchased seperately at an additional cost. The cost varies from course to course but is generally in between GBP 20 to GBP 40 per month.

Q17. Does your course guarantee a job?
A17. Our course is designed to provide you with a solid foundation in the subject and equip you with valuable skills. While the course is a significant step toward your career goals, its important to note that the job market can vary, and some positions might require additional certifications or experience. Remember that the job landscape is constantly evolving. We encourage you to continue learning and stay updated on industry trends even after completing the course. Many successful professionals combine formal education with ongoing self-improvement to excel in their careers. We are here to support you in your journey!

Q18. Do you provide placement services?
A18. While our course is designed to provide you with a comprehensive understanding of the subject, we currently do not offer placement services as part of the course package. Our main focus is on delivering high-quality education and equipping you with essential skills in this field. However, we understand that finding job opportunities is a crucial aspect of your career journey. We recommend exploring various avenues to enhance your job search:
a) Career Counseling: Seek guidance from career counselors who can provide personalized advice and help you tailor your job search strategy.
b) Networking: Attend industry events, workshops, and conferences to build connections with professionals in your field. Networking can often lead to job referrals and valuable insights.
c) Online Professional Network: Leverage platforms like LinkedIn, a reputable online professional network, to explore job opportunities that resonate with your skills and interests.
d) Online Job Platforms: Investigate prominent online job platforms in your region and submit applications for suitable positions considering both your prior experience and the newly acquired knowledge. e.g in UK the major job platforms are Reed, Indeed, CV library, Total Jobs, Linkedin.
While we may not offer placement services, we are here to support you in other ways. If you have any questions about the industry, job search strategies, or interview preparation, please dont hesitate to reach out. Remember that taking an active role in your job search process can lead to valuable experiences and opportunities.

Q19. How do I enrol in Uplatz video courses?
A19. To enroll, click on "Buy This Course," You will see this option at the top of the page.
a) Choose your payment method.
b) Stripe for any Credit or debit card from anywhere in the world.
c) PayPal for payments via PayPal account.
d) Choose PayUmoney if you are based in India.
e) Start learning: After payment, your course will be added to your profile in the student dashboard under "Video Courses".

Q20. How do I access my course after payment?
A20. Once you have made the payment on our website, you can access your course by clicking on the "My Courses" option in the main menu or by navigating to your profile, then the student dashboard, and finally selecting "Video Courses".

Q21. Can I get help from a tutor if I have doubts while learning from a video course?
A21. Tutor support is not available for our video course. If you believe you require assistance from a tutor, we recommend considering our live class option. Please contact our team for the most up-to-date availability. The pricing for live classes typically begins at USD 999 and may vary.

Premium Career Track - Chief Technology Officer (CTO)

Preview Premium Career Track - Chief Technology Officer (CTO) course

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