Machine Learning Course in Chennai

Intellipaat Machine Learning course in Chennai will help you be a master in the concepts and techniques of Machine Learning with Python. This includes ML algorithms, supervised and unsupervised learning, probability, statistics, decision tree, random forest, linear and logistic regression through real-world hands-on projects. Get the best Machine Learning training in Chennai from top data scientists.

Key Features

32 Hrs Instructor Led Training
32 Hrs Self-paced Videos
64 Hrs Project work & Exercises
Certification and Job Assistance
Flexible Schedule
Lifetime Free Upgrade
24 x 7 Lifetime Support & Access

About Machine Learning Course

Intellipaat is a leading e-learning institute providing one of the best Machine Learning Courses in Chennai, India. You will learn about Machine Learning with Python programming, supervised and unsupervised learning, Support Vector Machines, Random Forest Classifiers, best practices of Machine Learning, and more through hands-on projects and case studies.

What will you learn in this Machine Learning course in Chennai?

In Intellipaat Machine Learning Classes in Chennai, you will learn about:

  1. Fundamentals of using data to train machines
  2. Representation of an artificial neural network
  3. Linear regression with multiple variables using Python
  4. Logistic regression for classifying data using Python
  5. Support Vector Machines algorithms
  6. Designing of a Machine Learning system
  7. Principle Component Analysis for data modeling.

Intellipaat, one of the leading Machine Learning Institutes in Chennai offers a ML course which can be joined by:

  • Professionals in Analytics, Data Science, E-commerce, and Search Engine domains
  • Software Professionals looking for a career switch and fresh graduates.

Anybody can take up this training course regardless of their prior skills. However, basic programming skills can be helpful.

Chennai which is located on India’s east coast is home to a thriving technology sector, comprising the largest IT parks in Asia. Since research and analytics are vital parts of organizational processes which cannot be completed without statistical calculations, Machine Learning with Python has gained immense prominence in this market. Therefore, candidates who have sound knowledge in Machine Learning with Python will get ample opportunities in this city. Also, by having a Machine Learning certification in Chennai, it increases the possibilities of getting employed.

Chennai is the second largest exporter of software, after Bangalore. India’s top software companies have most of their operations in this city. The focus of multinational firms in this city has created a huge competition which can be managed by analyzing the market conditions. Machine Learning with Python programming serves this purpose, and hence aspirants wanting to become successful Data Scientists should learn Machine Learning with Python.

Machine Learning is one of the most important domains that is being deployed in today’s hyper competitive world. Be it for self-driving cars or for search engines like Google, Machine Learning is being extensively used for making our lives simple. Intellipaat is offering a comprehensive Machine Learning course in Chennai that can be taken up by professionals to excel in their careers and grab the best jobs in the industry.

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Course Fees

Self Paced Training

  • 32 Hrs e-learning videos
  • Lifetime Free Upgrade
  • 24 x 7 Lifetime Support & Access

Online Classroom preferred

  • Everything in self-paced, plus
  • 32 Hrs of instructor-led training
  • 1:1 doubt resolution sessions
  • Attend as many batches for Lifetime
  • Flexible Schedule
  • 31 May
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
  • 06 Jun
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
  • 14 Jun
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
$351 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 support
  • Strong Reporting

Machine Learning Course Content

Module 01 - Introduction to Machine Learning preview videos

1.1 Need of Machine Learning
1.2 Introduction to Machine Learning
1.3 Types of Machine Learning, such as supervised, unsupervised and reinforcement learning, why Machine Learning with Python and applications of Machine Learning.

2.1 Introduction to supervised learning, types of supervised learning, such as regression and classification
2.2 Introduction to regression,
2.3 simple linear regression,
2.4 Multiple linear regression, assumptions in linear regression
2.5 Math behind linear regression.

Hands-on Exercise

1. Implementing linear regression from scratch with Python
2. Using Python library Scikit-learn to perform simple linear regression and multiple linear regression
3. Implementing train–test split and predicting the values on the test set.

3.1 Introduction to classification
3.2 Linear regression vs Logistic regression
3.3 Math behind logistic regression, detailed formulas, log it function and odds, confusion matrix and accuracy, true positive rate, false positive rate, and threshold evaluation with ROCR.

Hands-on Exercise

1. Implementing logistic regression from scratch with Python
2. Using Python library Scikit-learn to perform simple logistic regression and multiple logistic regression
3. Building a confusion matrix to find out accuracy, true positive rate, and false positive rate.

4.1 Introduction to tree-based classification
4.2 Understanding a decision tree, impurity function, entropy, to understand the concept of information gain for the right split of node, impurity function, information gain
4.3 Understand the concept of information gain for the right split of node, impurity function, Gini index, to understand the concept of Gini index for the right split of node, overfitting, pruning, pre-pruning, post-pruning, cost-complexity pruning
4.4 Introduction to ensemble techniques, understanding bagging, introduction to random forests, and finding the right number of trees in a random forest.

Hands-on Exercise

1. Implementing a decision tree from scratch in Python
2. Using Python library Scikit-learn to build a decision tree and a random forest.
3. Visualizing the tree and changing the hyper parameters in the random forest.

5.1 Introduction to probabilistic classifiers,
5.2 Understanding Naïve Bayes, math behind the Bayes theorem
5.3 Understanding a support vector machine (SVM)
5.4 Kernel functions in SVM, and math behind SVM.

Hands-on Exercise

1. Using Python library Scikit-learn to build a Naïve Bayes classifier and a support vector classifier.

6.1 Types of unsupervised learning, such as clustering and dimensionality reduction, types of clustering
6.2 Introduction to k-means clustering
6.3 Math behind k-means
6.4 Dimensionality reduction with PCA.

Hands-on Exercise

1. Using Python library Scikit-learn to implement K-means clustering
2. Implementing PCA (principal component analysis) on top of a dataset.

7.1 Introduction to Natural Language Processing (NLP)
7.2 Introduction to text mining
7.3 Importance and applications of text mining
7.4 How NPL works with text mining
7.5 Writing and reading to word files
7.6 OS modules, Natural Language Toolkit (NLTK) environment,
7.7  Text mining: its cleaning and pre-processing and text classification.

Hands-on Exercise

1. Learning Natural Language Toolkit and NLTK Corpora
2. Reading and writing .txt files from/to a local drive
3. Reading and writing .docx files from/to a local drive.

8.1 Introduction to Deep Learning with neural networks
8.2 Biological neural network vs artificial neural network
8.3 Understanding perception learning algorithm, introduction to Deep Learning frameworks, and Tensor Flow constants, variables and place-holders.

9.1 What is time series?, its techniques and applications
9.2 Time series components
9.3 Moving average, smoothing techniques, exponential smoothing
9.4 Univariate time series models
9.5 Multivariate time series analysis
9.6 ARIMA model, time series in Python
9.7 Sentiment analysis in Python (Twitter sentiment analysis), and text analysis.

Hands-on Exercise

1. Analyzing time series data
2. The sequence of measurements that follow a non-random order to recognize the nature of phenomenon
3. Forecasting the future values in the series.

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Machine Learning Projects and Case Studies

What projects and case studies I will be working on in this Machine Learning certification course?

Project 01: Analysing the trends of COVID-19 with Python

Industry: Analytics

Problem Statement: Understanding, the trend of covid 19 spread and if the restrictions imposed by governments around the world has helped us curb the COVID cases and by what degree

Topics: In this project we will use Data Science and Python perfrom visualization to better understand the data we currently have on COVID 19 as well as using Time Series Analysis in order to make a perdiction about future cases if the current trend as observed thus far continues.


  • Using pandas to accumulate data from multiple data files
  • Using plotly (visualization library) to create interactive visualizations
  • Using facebooks prophet library to make timeseries models
  • Visualzing the perdiction by combining these technologies

Project 02 – Customer Churn Classification

Topics – This is a real-world project that gives you hands-on experience in working with most of the Machine Learning algorithms.

The main components of the project include the following:

  • Manipulating data in order to gain meaningful insights.
  • Visualizing data to figure out trends and patterns among different factors.
  • Implementing these algorithms: linear regression, decision tree, and Naïve Bayes.

Project 03 – Recommendation for Movie, Summary

Topics – This is a real-world project that gives you hands-on experience in working with a movie recommender system. Depending on what movies are liked by a particular user, you will be in a position to provide data-driven recommendations. This project requires you to deeply understand information filtering, recommender systems, user ‘preference’, and more. You will exclusively work on data related to user details, movie details, and others.

The main components of the project include the following:

  • Recommendation for movies
  • Two types of predictions: Rating prediction and item prediction
  • Important approaches: Memory-based and model-based
  • Knowing user-based methods in K-Nearest Neighbor
  • Understanding the item-based method
  • Matrix factorization
  • Decomposition of singular value
  • Data Science project discussion
  • Collaboration filtering
  • Business variables overview

Case Study 01 – Decision Tree

Topics – To understand the structure of a dataset (PIMA Indians Diabetes database) and create a decision tree model based on it by using Scikit-learn

Case Study 02 – Insurance Cost Prediction (Linear Regression)

Topics – To understand the structure of a medical insurance dataset, implement both simple and multiple linear regression, and predict values

Case Study 03 – Diabetes Classification (Logistic Regression)

Topics – To understand the structure of a dataset (PIMA Indians Diabetes dataset), and implement multiple logistic regression and classify[I3] . Fit your model on the test and train data for prediction and evaluate your model using confusion matrix and then visualize it

Case Study 04 – Random Forest

Topics – To create a model that would help in classifying whether a patient is ‘Normal’, ‘Suspected to have disease,’ or in actuality ‘Has the disease’ on the ‘Cardiotocography’ dataset

Case Study 05 – Principal Component Analysis (PCA)

Topics – Read the sample iris dataset given to you, use PCA to figure out the number of most important principal features, and then reduce the number of features using PCA. Train and test the Random Forest Classifier algorithm to check if reducing the number of dimensions is causing the model to perform poorly. Figure out the most optimal number that produces good quality results and predicts accuracy

Case Study 06 – K-means Clustering


  • Analyze data
  • Extract useful columns from the dataset
  • Visualize data
  • Find out the appropriate number of groups or clusters for data to be segmented into (using the elbow method)
  • Using k-means clustering, segment data into k groups (k is found in the previous step)
  • Visualize a scatter plot of clusters, and a lot more
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Machine Learning Certification

Intellipaat’s course on Machine Learning, which is one of the best Machine Learning Courses is designed by industry professionals that will help you get the best jobs in top MNCs. As part of this ML training, you will be engaged in real-time projects and assignments that have huge implications in real-world industry scenarios. This way, you can expedite your career effortlessly.

At the end of this ML certification training course, you will find a quiz test that perfectly reflects the type of questions asked in the Machine Learning Certification exam, it will further help get a higher score.

Intellipaat Course Completion Certification will be issued after the project has been completed (after expert review) and upon scoring at least 60 percent on the quiz. You would be glad to know that Intellipaat certification is recognized by more than 100 top multinational companies, including Cisco, Ericsson, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered Bank, IBM, Infosys, Genpact, TCS, Hexaware and more.

Our Alumni works at top 3000+ companies

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Machine Learning Training Reviews


Mr Yoga


John Chioles




Dileep & Ajay

Raghavendra Narayan

Business Analyst at Tata Consultancy Services

They provide one of the best Machine Learning online courses in the market. I really liked the way Intellipaat approached such a complex topic like Machine Learning and made it so easy to understand. 5 stars to Intellipaat for conducting such wonderful Machine Learning classes.

Rashi G

Intellipaat's Machine Learning online training helped me clear the exam in the first attempt. Also, the trainer came with very good experience, and thus, I was able to learn this technology effortlessly. Thank you Intellipaat!

Bharat Rathore

Expert in Data Analysis & Data Science

The Machine Learning online certification classes was top-notch and the course material was very good with lots of real-world examples of this awesome technology. Learning with Intellipaat was a great experience!

Frequently Asked Questions on Machine Learning

Why should I learn Machine Learning from Intellipaat?

Intellipaat provides comprehensive Machine Learning training through hands-on projects and case studies. A few of the many reasons for choosing Intellipaat ML course includes:

  • You will learn various concepts such as Machine Learning using Python, Classification techniques, Linear and Logistic Regression, Supervised and Unsupervised Learning, and more
  • After successfully completing your Machine Learning online training, you will be awarded Intellipaat Machine Learning Certification, which holds merits across 100+ MNCs across the world
  • This course covers real-time ML projects and step-by-step tasks that are highly relevant to the corporate world, as well as a curriculum for this course, are created by industry experts
  • Our Machine Learning certificate will allow you to compete for the highest salary for some of the best positions in the world’s leading MNCs
  • We provide lifetime access to videos, course materials, 24/7 learning support and free upgrades to the latest version.
At Intellipaat you can enroll either for the instructor-led online training or self-paced training. Apart from this Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience and they have been actively working as consultants in the same domain making them subject matter experts. Go through the sample videos to check the quality of the trainers.
Intellipaat is offering the 24/7 query resolution and you can raise a ticket with the dedicated support team anytime. You can avail the email support for all your queries. In the event of your query not getting resolved through email we can also arrange one-to-one sessions with the trainers. You would be glad to know that you can contact Intellipaat support even after completion of the training. We also do not put a limit on the number of tickets you can raise when it comes to query resolution and doubt clearance.
Intellipaat offers the self-paced training to those who want to learn at their own pace. This training also affords you the benefit of query resolution through email, one-on-one sessions with trainers, round the clock support and access to the learning modules or LMS for lifetime. Also you get the latest version of the course material at no added cost. The Intellipaat self-paced training is 75% lesser priced compared to the online instructor-led training. If you face any problems while learning we can always arrange a virtual live class with the trainers as well.
Intellipaat is offering you the most updated, relevant and high value real-world projects as part of the training program. This way you can implement the learning that you have acquired in a real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning and practical knowledge thus making you completely industry-ready. You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. Upon successful completion of the projects your skills will be considered equal to six months of rigorous industry experience.
Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this we are exclusively tied-up with over 80 top MNCs from around the world. This way you can be placed in outstanding organizations like Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation part as well.
You can definitely make the switch from self-paced to online instructor-led training by simply paying the extra amount and joining the next batch of the training which shall be notified to you specifically.
Once you complete the Intellipaat training program along with all the real-world projects, quizzes and assignments and upon scoring at least 60% marks in the qualifying exam; you will be awarded the Intellipaat verified certification. This certificate is very well recognized in Intellipaat affiliate organizations which include over 80 top MNCs from around the world which are also part of the Fortune 500 list of companies.
Apparently, No. Our Job Assistance program is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and assists you in finding a well-paid job, matching your profile. The final decision on your hiring will always be based on your performance in the interview and the requirements of the recruiter.
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