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Machine Learning with Python Programming

35 Hours
Online Instructor-led Training
USD 742
Machine Learning with Python Programming course and certification
1 Learner

About this Course
Machine learning (ML) is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.Python is one of the most commonly used languages to build machine learning systems.
In this course you will learn all the concept of Python programming and Machine learning from basic to advanced level.

Machine Learning with Python Programming

Course Details & Curriculum

Machine Learning with Python Programming- syllabus


Python Programming (Part-1)


Introduction to Python Programming

What is Python Programming?

History of Python Programming

Features of Python Programming

Why to learn Python Programming

Application of Python Programming

Setup of Python Programming

Getting Python

Installation of Python

Getting started with the first Python program

Running 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

- elif statement


Introduction to loops

Types of loops

- for loop

- while loop

- infinite loop

- nested loop

Break, continue and pass statement

Python programs for all types of loops


Number Type Conversion

Random Number Functions

Trigonometric Functions

Mathematical Constants


Accessing Values in Strings

Updating Strings

String Special Operators

Built-in String Methods


Python Lists

Accessing Values in Lists

Updating Lists

Deleting List Elements

Basic List Operations

Built-in List Functions and Methods


Accessing Values in Tuples

Updating Tuples

Deleting Tuple Elements

Basic Tuples Operations               

Built-in Tuple Functions

Difference between list and tuple



Accessing Values in Dictionary

Updating Dictionary

Delete Dictionary Elements

Properties of Dictionary Keys

Built-in Dictionary Functions and Methods


Defining a Function

Calling a Function

Passing by Reference versus Passing by Value

Ways to write function

Types of functions

Anonymous function

Recursive Function


What is a module?

Creating a module

The import Statement

The ‘from’ import Statement

Renaming a module

Using the dir() function

The ‘from’ import * Statement

Locating Modules


Printing to the Screen

Opening and Closing Files

The open Function

The file Object Attributes

The close() Method

Reading and Writing Files

The write() Method

The read() Method





match() function

search() function

re.match() vs re.search()

findall() function

split() function

sub() function


Machine Learning (Part-2)


Introduction to Machine Learning

What is a Machine Learning?

Need for Machine Learning

Why & When to Make Machines Learn?

Challenges in Machines Learning

Application of Machine Learning

Types of Machine Learning

Types of Machine Learning

      Supervised learning

      Unsupervised learning

      Reinforcement learning

Difference between Supervised and Unsupervised learning


Components of Python ML Ecosystem

Using Pre-packaged Python Distribution: Anaconda

Jupyter Notebook




Regression Analysis (Part-I)

Regression Analysis

Linear Regression

Examples on Linear Regression

scikit-learn library to implement simple linear regression

Regression Analysis (Part-II)

Multiple Linear Regression

Examples on Multiple Linear Regression

Polynomial Regression

Examples on Polynomial Regression

Classification (Part-I)

What is Classification

Classification Terminologies in Machine Learning

Types of Learner in Classification

Logistic Regression

Example on Logistic Regression

Classification (Part-II)

What is KNN?

How does the KNN algorithm work?

How do you decide the number of neighbors in KNN?

Implementation of KNN classifier

What is a Decision Tree?

Implementation of Decision Tree

SVM and its implementation

Clustering (Part-I)

What is Clustering?

Applications of Clustering

Clustering Algorithms

K-Means Clustering

How does K-Means Clustering work?

K-Means Clustering algorithm example

Clustering (Part-II)

Hierarchical Clustering

Agglomerative Hierarchical clustering and how does it work

Woking of Dendrogram in Hierarchical clustering

Implementation of Agglomerative Hierarchical Clustering

Association Rule Learning

Association Rule Learning

Apriori algorithm

Working of Apriori algorithm

Implementation of Apriori algorithm

Recommender Systems

Introduction to Recommender Systems

Content-based Filtering

How Content-based Filtering work

Collaborative Filtering

Implementation of Movie Recommender System


Machine Learning with Python Programming

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

Career Path

The market for Artificial Intelligence and Machine Learning is extremely hot right now. The demand for talented and skilled professionals in Machine Learning is at its peak now, and in the future, it will only escalate higher. The great thing about a Machine Learning career is that apart from job satisfaction and security, it also promises hefty annual compensation and fast career growth. All the more reason to consider building a Machine Learning career path. 

Once you have acquired the right ML skills, here are the top five promising Machine Learning career paths that you can aspire for:
1. Machine Learning Engineer
2. Data Scientist
3. Software Developer/Engineer (AI/ML)
4. Human-Centered Machine Learning Designer

Job Prospects

According to a 2019 Indeed report, Machine Learning Engineer is the #1 job in the list of The Best Jobs in the US, recording a whopping 344% growth with a median salary of $146,085 per year. In India, the national average salary for Machine Learning jobs is ₹11,05,748.

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