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Machine Learning Course

84,225 Ratings

Rated #1 Machine Learning Training by India TV

  • Learn industry-relevant skills from Microsoft’s SMEs and IIT Professors.
  • Access 24/7 support for any technical problems and doubt resolution.
  • Get assured placement assistance to obtain your dream job.
  • Practical tasks will help you master Python, machine learning techniques, artificial intelligence, and statistics.
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Key Features

50+ live sessions over 7 months.
218 hours of self-paced video content.
200 hours of hands-on projects and exercises.
Learn from industry experts.
Participate in Hackathons.
1:1 sessions with industry mentors.
Career guidance and job assistance.
24/7 technical support.
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Machine Learning Course Overview

This Machine Learning course is specially designed by Microsoft’s SMEs and industry experts to help learners upgrade their skills in Machine Learning, Deep Learning, NLP, Generative AI, and Prompt Engineering.

What skills will you master in this Machine Learning Course?

The course is designed by Industry professionals to provide a solid foundation of machine learning concepts. Here are the skills that you will master in this course.

  • You will be able to analyse, manipulate, and preprocess data using tools such as Python, SQL, PowerBI, and Excel.
  • You will master statistics and linear algebra concepts, laying a foundation for machine learning algorithms.
  • You will gain a deep understanding of machine learning algorithms and concepts.
  • You will understand major deep learning algorithms and concepts like neural networks using TensorFlow.
  • You will acquire skills to deploy machine learning models on cloud platforms like Microsoft Azure.
  • You will be able to create end-to-end machine learning and deep learning industry-relevant projects and hackathons.

Over 7 months, you will be covering the following courses:

  • Course 01 – Programming Basics for Machine Learning – Python
  • Course 02 – Data Wrangling using SQL
  • Course 03 – Creating an Interactive Dashboard using PowerBI and Excel
  • Course 04 – Data Manipulation and Visualization using Numpy, Pandas, Matplotlib and Seaborn
  • Course 05 – Linear Algebra and Statistics
  • Course 06 – Overview of Machine Learning
  • Course 07 – Supervised and unsupervised machine learning algorithms
  • Course 08 – Deep Learning using TensorFlow
  • Course 09 – Natural Language Processing (NLP)
  • Course 10 – Deploying machine learning models on the cloud (MLOps)
  • Course 11 – Generative AI
  • Course 12 – Prompt Engineering

Data science is one of the industry’s booming fields, and machine learning is a core part of it.

According to Statista, the projected market size of machine learning will be USD 79.29 billion in 2024 and USD 503.40 billion by 2030, with a CAGR of 36.08%. According to the McKinsey Global Survey 2024, 65% of companies regularly use machine learning and AI in their organisation.

LinkedIn states that there are 134000+ open job roles for machine learning professionals in India. Lastly, according to Naukri, the average salary of a machine learning engineer is INR 12,00,000.

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Machine Learning engineers rank among the top emerging jobs. - LinkedIn
The market size in the Machine Learning market is projected to reach US$105.45bn in 2025. - Statista

Machine Learning Career Transitions

57% Average Salary Hike

$1,14,000 Highest Salary

12000+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Meet Your Course Mentors

Hari Prasad Piridi

Hari Prasad Piridi

Director, Data Science at Walmart

Hari is a machine learning expert with 20 years of experience leading high-impact AI initiatives at Walmart, Microsoft, and Merrill Lynch. Specializes in applied ML, GenAI, time series forecasting, and large-scale data science solutions using Python.

Akash Pushkar

Akash Pushkar

Principal Data Scientist at Accenture

Akash Pushkar, an IIT Kanpur graduate and principal data scientist at Accenture, brings 11 years of expertise in AI, deep learning, and TensorFlow. He specializes in machine learning algorithms, NLP, computer vision, and deploying AI models in production.

Ankit Tanmay 1

Ankit Tanmay

Data and Applied Scientist 2 at Microsoft

Ankit is a data scientist with 10 years of experience delivering data-driven solutions using Python for Fortune 500 companies. Expertise in predictive analytics, machine learning, and data visualization with tools like Python, Tableau, and Power BI.

AJAY BHARAJ

Ajay Bharaj

Data Science Specialist at Ex-McKinsey & Company

Ajay is a machine learning data scientist with 10 years of experience at Bain, McKinsey, and Sopra Steria. With an MTech in AI from IIT Jodhpur, he is also an expert in Python and predictive modeling, with a focus on digital transformation.

Abhinav Harsh

Abhinav Harsh

Lead Data Scientist at Fractal Analytics

Abhinav is a data scientist with 14 years of experience, currently leading advanced analytics initiatives at Fractal Analytics. He is an expert in retail and consumer goods, specializing in personalized solutions, customer retention, and business growth through data-driven strategies.Read More

18+ Key Skills You'll Master

Python

Data Science

Data Analysis

Generative AI

GIT

MLOps

Data Wrangling

SQL

Machine Learning

Prediction algorithms

Natural Language Processing

Data Visualisation

Speech Recognition

Reinforcement Learning

Recommendation Systems

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9+ Essential Tools You'll Learn

python 2 jupyter 3 Scipy 2 numpy 2 pandas matplotlib Keras tensorflow SQL 1 openai excel 1 Frame 3 PowerBI Langchain

Machine Learning Course Fees

Online Classroom Preferred

Weekend (Sat-Sun)

12 Jul 2025 08:00 PM - 11:00 PM
Weekend (Sat-Sun)

19 Jul 2025 08:00 PM - 11:00 PM
Weekend (Sat-Sun)

26 Jul 2025 08:00 PM - 11:00 PM
Weekend (Sat-Sun)

02 Aug 2025 08:00 PM - 11:00 PM
₹70,053 10% OFF Expires in

EMI Starts at

₹5,000

We partnered with financing companies to provide very competitive finance options at 0% interest rate

Financing Partners

EMI Partner

The credit facility is provided by a third-party financing company and any arrangement with such financing companies is outside Intellipaat’s purview.

Corporate Training

  • Customized Learning
  • Enterprise Grade Learning Management System (LMS)
  • 24x7 Support
  • Enterprise Grade Reporting

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Machine Learning Course Syllabus

Live Course Industry Expert Academic Faculty

Machine Learning Prerequisites - Python Basics

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  • Get introduced to basic programming terminologies and concepts like variables, data types, operators, functions, etc.
  • Understand the implementation of the object-oriented programming (OOPS) concept.
  • By the end of this module, you should be able to create programs in Python.
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  • Learn the fundamentals of Structured Query Language (SQL) such as tables, joins, comments, operators, DDL (Data Definition Language), DQL (Data Query Language), DML (Data Manipulation Language), DCL (Data Control Language) and TCL (Transaction Control Language)
  • Understand and Implement subqueries, rules, views, pattern matching, UDFs, stored procedures, etc.
  • Optimise your SQL queries by indexing, grouping, sorting, and CTEs(Common Table Expressions).
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  • Learn to manipulate data and create interactive visualisations using Python libraries like Numpy, Pandas, Matplotlib, and Seaborn.
  • Understand essential preprocessing techniques, such as exploratory data analysis, feature engineering, scaling, normalisation, and standardisation.
  • Using Python libraries, create bar charts, scatter plots, count plots, line plots, pie charts, doughnut charts, and more.
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  • Understand descriptive statistical measures such as central tendency, spread, five-point summary, etc.
  • Learn about inferential statistical measures such as correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, and chi-square test.
  • Analyse the probability of an event using probability distribution, Bayes’s theorem and central limit theorem.
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  • Get Introduced to machine learning, its types and usage.
  • Learn about regression, classification and clustering. Learn how to pick the right algorithms for a given problem statement.
  • Create a machine learning model for each of them and understand how to train, evaluate, and optimise them.
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  • Deep Dive into different machine learning algorithms and understand their working, importance and usage.
  • Learn and Implement supervised machine learning algorithms such as Linear regression, Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, Gradient Descent, K-nearest neighbours, and Time Series Forecasting.
  • Learn and Implement different unsupervised machine learning algorithms, such as K-means, Dimensionality reduction, linear discriminant analysis, Principal Component Analysis, etc.
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  • Understand and learn the basics of Artificial Intelligence and Python libraries like Keras and TensorFlow.
  • Learn the essential concepts of neural networks, such as their definition, advantages, structure, usage, types, etc.
  • Implement crucial deep learning concepts, such as Deep neural networks, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), GPUs in deep learning, Autoencoders, Restricted Boltzmann machines, etc.
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  • Explore the fundamentals of generative AI like LSTM, transformer architecture, BERT, etc.
  • Understand why these Gen AI models are better than traditional machine learning models.
  • Implement and learn about the evolution of large language models (LLMs) and their architecture to better understand context and perform complex generation tasks.
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  • Understand the basic concepts of NLP, such as tokenisers, POS tagging, lemmatisation, trigrams, Ngrams, text classification, stemming, frequency distribution, etc.
  • Work with language models, sequencing tasks, syntax trees, chunking, chinking, context-free grammar, etc.
  • Learn about the mechanism of words, term frequency, text conversion, count vectoriser, inverse document, etc.
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  • Learn the basics of Prompt Engineering.
  • Explore various strategies for prompt design.
  • Understand methods for evaluating prompt effectiveness and applying feedback loops to optimise the output.
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  • Understand the fundamental workings of MLOps and its lifecycle, from developing the model to evaluating and deploying it over Azure Machine Learning.
  • Get introduced to Microsoft Azure Machine Learning service and deploy your first machine learning model on it.
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In this machine learning capstone project, you will create an end-to-end machine learning pipeline. You will analyse the problem and suggest solutions based on data insights.

  • You will start by extracting and loading the data, followed by transforming it into a format suitable for driving inferences.
  • The next step will be manipulating and preprocessing the data to prepare it for creating a model.
  • Before creating the machine learning model, we must perform feature engineering related to the problem statement.
  • Then, we will select a suitable model that fits the problem statement and the data, train it with the training dataset, and test it using the testing dataset.
  • The last step is to evaluate the model and monitor it so that it gives a proper outcome.
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Electives:

  • Get introduced to PowerBI basics like importing data and creating dashboard reports for practical business intelligence.
  • Understand the usage of Data Analysis Expressions (DAX) to create custom metrics and perform calculations.
  • Create a PowerBI dashboard from scratch using everything you have learnt in this module, from creating visualisations, slicers, DAX, etc.
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  • You will be armed with some of the best job search strategies to help you search for jobs efficiently.
  • Create ATS friendly resume and LinkedIn profile that will increase your visibility in the industry market.
  • Give multiple mock interviews to industry professionals to get acclimatised to the types of questions and the interview environment.
  • Grab placement opportunities with our network of 3100+ hiring partners on clearing the placement readiness test (PRT).
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  • Learn the basics of MS Excel, such as getting familiar with the interface, formatting cells, alignments, sorting, filters, and fonts.
  • Implement and understand formulae and functions that make your Excel workbook dynamic.
  • Learn to create chart illustrations and apply data validation rules and conditional formatting for better trend analysis.
  • Make use of Excel for classification and regression problems.
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Placement Assistance
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Exclusive access to Intellipaat Job portal
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1 on 1 Career Mentoring Sessions
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Career Oriented Sessions
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Resume & LinkedIn Profile Building
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Machine Learning Certification

What certifications will I receive after completing this program?

After completing the course on machine learning, you will be awarded the following certificates:

  • Microsoft Certificate for Power BI.
  • Microsoft Certificate for SQL.
  • Industry-recognized Machine Learning Certification by Intellipaat & NSDC

These recognized certifications will help you showcase your skills to employers and help you crack top jobs.

Reviews & Testimonials

(84,225)
Aryan Shinde

Aryan Shinde

Investment Proof Audit Specialist at HGS

Completing Intellipaat's rewarding Online Machine Learning Course offered deep insights into ML algorithms and neural networks. The practical experience with Scikit-Learn and TensorFlow was incredibly valuable.

K Nikhil Sai Reddy

K Nikhil Sai Reddy

Software Engineer at Blackhawk Network India

The MIT IDSS Machine Learning course by Intellipaat was a deep dive into ML concepts, from basics to advanced deep learning techniques. The hands-on projects and real-world datasets truly sharpened my practical skills.

Mayank Sharma

Mayank Sharma

Data Analyst at Rajasthan Fasteners Private Limited

Earning the Post Graduate Certification in Data Science & ML from EICT MNIT Jaipur with Intellipaat is a proud achievement. Its focus on practical, real-world applications was invaluable for boosting my data science skills and comprehension.

Suganthi Su

Suganthi Su

Associate Professor at Sri Sai Ram Institute of Technology

Earning the Post Graduate Certification in Data Science & ML from EICT Academy MNIT Jaipur with Intellipaat is a proud achievement. The focus on real-world, practical applications was invaluable for enhancing my data science skills.

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Machine Learning Training FAQs

Why should I join this course at Intellipaat?

Here are a few reasons:

  • Get an end-to-end understanding of all the machine learning concepts, from scraping data to deploying the model over the cloud.
  • Get extensive hands-on and case studies that will help you understand industry standards.
  • Learn from the best industry experts.
  • Earn an industry-recognised Intellipaat & Microsoft
  • Get 24*7 support to clear out your doubts.

Machine learning is being used in almost every sector nowadays. This covers medical diagnostics, facial recognition, weather forecasting, image processing, and other applications. Machine learning can be useful in any circumstance that requires pattern identification, prediction, or analysis. With proper information, machine learning technology can uncover exceedingly complicated patterns and generate highly accurate predictions.

Read more about Machine Learning

A Machine Learning Engineer designs, develops, and deploys machine learning models to solve real-world problems. They work with large datasets, build algorithms, and fine-tune models for optimal performance. Key tasks include training models, implementing advanced technologies like RAG (Retrieval-Augmented Generation) and LangChain, and applying machine learning techniques for projects such as Customer Segmentation. Their work bridges the gap between data science and software engineering, ensuring machine learning solutions are scalable, efficient, and integrated into business processes.

Learn How to become a successful Machine Learning Engineer

This Machine Learning course features 12+ real-world projects, including cutting-edge applications in RAG (Retrieval-Augmented Generation), LangChain, and Customer Segmentation. Gain hands-on experience with the latest ML technologies while building practical, industry-relevant solutions

Some top sectors for AI and Machine Learning professionals include technology, finance, healthcare, retail, automotive, marketing, manufacturing, and energy. These sectors utilise AI for various purposes, such as optimisation, prediction, and automation, to stay competitive and deliver more customised services.

Learn about the Future Scopes of Machine Learning

Intellipaat provides several practice tests as part of this machine learning course. These practice tests will help you better understand the concepts and make you industry-ready.

Check out our Free Data Science Course with Certificate

There are no such prerequisites to get into this machine learning course. This course will provide you with all the coding knowledge required in this domain. But, being familiar with coding will be a plus.

Does Machine Learning Requires Coding or Not?

Python is the most used language for machine learning.  Engineers that create machine learning systems frequently combine Jupyter Notebooks and Python.  Jupyter Notebooks is a web application that allows you to explore by creating and sharing documents with live code, equations, and more.

Learn about the Top Programming Languages in Machine Learning

Your instructors will include esteemed professors from IITs and industry experts from leading multinational companies such as Google, Microsoft, Nvidia, Cisco, and others.

The duration for this online Machine Learning Training typically takes seven months of instructor-led training.

This machine learning course from Intellipaat is designed by best industry experts. The course is designed in such a way that it will take you from beginner level to advanced level slowly but steadily. It covers all the essential topics to make you industry-ready. Our faculty uses real-life examples, case studies and practice sets to ensure industry standards are met. So, if you aspire to become one and are new in this field, this is the best course for you.

Check out our Machine Learning Tutorial for Beginners

The labs from this machine learning training are integrated into the platform. These labs will cater to your hands-on projects, practice sets, etc., to make you industry-ready. You will also be guided on how to use these labs and execute the hands-on demo.

Intellipaat offers 24/7 doubt-solving sessions. You can request a support session by creating a ticket or email [email protected] from your registered email ID. A support team member will reach out and help you with your queries. A support team member might schedule a one-on-one session or resolve your query over the phone. However, 1:1 support session is given for 6 months from the start date of your course.

Yes, all learners completing the course have to go through a PRT(Placement Readiness Test) to get into the placement pool. They will start getting opportunities soon after they are in the placement pool. More than 500+ top MNCs and startups are hiring Intellipaat learners. Our alumni work with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

No, job assistance doesn’t guarantee a job. It guarantees the potential opportunities you will get as a learner who has completed the course and passed the PRT. The final decision rests with the employer based on your performance in the interview.

Yes, as per our refund policy, once the enrollment is done, no refund is applicable.

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