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Data Science with Python

40 Hours
Online Instructor-led Training
USD 952
Data Science with Python course and certification
1 Learner

About this Course
In this course you will learn all the concept of
- Python Programming
- Data Visualisation
- Data Analysis
- Machine Learning
- Data Science Methodology
- Types of machine learning with implementation of various algorithms

Data Science with Python

Course Details & Curriculum

Data Science with Python Programming - syllabus


Introduction to Data Science

Introduction to Data Science

Python in Data Science

Why is Data Science so Important?

Application of Data Science

What will you learn in this course?

Introduction to Python Programming

What is Python Programming?

History of Python Programming

Features of Python Programming

Application of Python Programming

Setup of Python Programming

Getting started with the first Python program

Variables and Data types

What is a variable?

Declaration of variable

Variable assignment

Data types in Python

Checking Data type

Data types Conversion

Python programs for Variables and Data types.

Python Identifiers, Keywords, Reading Input, Output Formatting

What is an Identifier?


Reading Input

Taking multiple inputs from user

Output Formatting

Python end parameter

Operators in Python

Operators and types of operators

1. Arithmetic Operators

2. Relational Operators

3. Assignment Operators

4. Logical Operators

5. Membership Operators

6. Identity Operators

7. Bitwise Operators

Python programs for all types of operators


Introduction to Decision making

Types of decision making statements

Introduction, syntax, flowchart and programs for

- if statement

- if…else statement

- nested if

elif statement


Introduction to loops

Types of loops

- for loop

- while loop

- nested loop

Loop Control Statements

    Break, continue and pass statement

Python programs for all types of loops


Python Lists

Accessing Values in Lists

Updating Lists

Deleting List Elements

Basic List Operations

Built-in List Functions and Methods for list

Tuples and Dictionary

Python Tuple

Accessing, Deleting Tuple Elements

Basic Tuples Operations               

Built-in Tuple Functions & methods

Difference between List and Tuple

Python Dictionary

Accessing, Updating, Deleting Dictionary Elements

Built-in Functions and Methods for Dictionary

Functions and Modules

What is a Function?

Defining a Function and Calling a Function

Ways to write a function

Types of functions

Anonymous Functions

Recursive function         

What is a module?

Creating a module

import Statement

Locating modules

Working with Files

Opening and Closing Files

The open Function

The file Object Attributes

The close() Method

Reading and Writing Files





match() function

search() function

re.match() vs re.search()

findall() function

split() function

sub() function

Introduction to Python Data Science Libraries

Data Science Libraries

Libraries for Data Processing and Modeling

·         Pandas

·         Numpy

·         SciPy

·         Scikit-learn

Libraries for Data Visualization

·         Matplotlib

·         Seaborn

·         Plotly

Components of Python Ecosystem

Components of Python Ecosystem

Using Pre-packaged Python Distribution: Anaconda

Jupyter Notebook

Analysing Data using Numpy and Pandas

Analysing Data using Numpy & Pandas

·         What is numpy? Why use numpy?

·         Installation of numpy

·         Examples of numpy

·         What is ‘pandas’?

·         Key features of pandas

·         Python Pandas - Environment Setup

·         Pandas – Data Structure with example

·         Data Analysis using Pandas

Data Visualisation with Matplotlib

Data Visualisation with Matplotlib

       What is Data Visualisation?

       Introduction to Matplotlib

       Installation of Matplotlib

Types of data visualization charts/plots

       Line chart, Scatter plot

       Bar chart, Histogram

       Area Plot, Pie chart

       Boxplot, Contour plot

Three-Dimensional Plotting with Matplotlib

Three-Dimensional Plotting with Matplotlib

       3D Line Plot

       3D Scatter Plot

       3D Contour Plot

       3D Surface Plot

Data Visualisation with Seaborn

Introduction to seaborn

Seaborn Functionalities

Installing seaborn

Different categories of plot in Seaborn

Exploring Seaborn Plots

Introduction to Statistical Analysis

What is Statistical Analysis?

Introduction to Math and Statistics for Data Science

Terminologies in Statistics – Statistics for Data Science

Categories in Statistics


Mean, Median, and Mode


Data Science Methodology (Part-1)

Module 1: From Problem to Approach

·         Business Understanding

·         Analytic Approach

Module 2: From Requirements to Collection 

·         Data Requirements

·         Data Collection

Module 3: From Understanding to Preparation 

·         Data Understanding

·         Data Preparation


Data Science Methodology (Part-2)

Module 4: From Modeling to Evaluation

·         Modeling

·         Evaluation

Module 5: From Deployment to Feedback

·         Deployment

·         Feedback


Introduction to Machine Learning and its types

What is a Machine Learning?

Need for Machine Learning

Application of Machine Learning

Types of Machine Learning

·         Supervised learning

·         Unsupervised learning

·         Reinforcement learning

Regression Analysis

Regression Analysis

Linear Regression

Implementing Linear Regression

Multiple Linear Regression

Implementing Multiple Linear Regression

Polynomial Regression

Implementing Polynomial Regression


What is Classification?

Classification algorithms

Logistic Regression

Implementing Logistic Regression

Decision Tree

Implementing Decision Tree

Support Vector Machine (SVM)

Implementing SVM


What is Clustering?

Clustering Algorithms

K-Means Clustering

How does K-Means Clustering work?

Implementing K-Means Clustering

Hierarchical Clustering

Agglomerative Hierarchical clustering

How does Agglomerative Hierarchical clustering Work?

Divisive Hierarchical Clustering

Implementation of Agglomerative Hierarchical Clustering

Association Rule Learning

Association Rule Learning

Apriori algorithm

Working of Apriori algorithm

Implementation of Apriori algorithm            


Problem Statement


Exploratory Data Analysis

Implementation of Project

Data Science with Python

After the completion of this course, you will get the certification.

Career Path

The Data Scientist is an expert in various underlying fields of Statistics and Computer Science. He uses his analytical aptitude to solve business problems.
Data Scientist is well versed with problem-solving and is assigned to find patterns in data. His goal is to recognize redundant samples and draw insights from it. Data Science requires a variety of tools to extract information from the data. A Data Scientist is responsible for collecting, storing and maintaining the structured and unstructured form of data.The report from Indeed showed a 29% increase in demand for data scientists year over year and a 344% increase since 2013. Demand for data science professionals is growing, as organizations maintain themselves through data-driven insights. Once you have acquired the right Data science skills, here are the top five promising career paths that you can aspire for:
1. Machine Learning Engineer
2. Data Scientist
3. Software Developer/Engineer (AI/ML)
4. Data Engineer
5. Data Analyst

Job Prospects

According to Payscale.com,
The top respondents for the job title Data Scientist are from the companies Mu Sigma, Tata Consultancy Services Limited and Accenture. Reported salaries are highest at Amazon.com Inc where the average pay is ₹1,474,576. Other companies that offer high salaries for this role include HCL Technologies Ltd. and Accenture, earning around ₹1,200,000 and ₹1,179,162, respectively. Mu Sigma pays the lowest at around ₹650,000. EY (Ernst & Young) and Tata Consultancy Services Limited also pay on the lower end of the scale, paying ₹863,584 and ₹890,567, respectively.
According to Payscale.com, 
Average Data Scientist Salary in US is $96,303.
Accordng to glassdoor.com, 
The national average salary for a Data Scientist is $1,13,309 in United States. 
Accordng to indeed.com, 
The average salary for a data scientist is $122,832 per year in the United States.
The average salary for a data scientist is ₹ 7,48,855 per year in India.

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