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Pravartak

Machine Learning Course

84,075 Ratings

Rated #1 Machine Learning Training by India TV

Upskill yourself with this Machine Learning course to become a certified Machine Learning engineer in 7 months.

  • Get trained by eminent IIT Madras Faculty and industry experts
  • Master Python, machine learning algorithms, statistics, AI & more
  • Guaranteed Placement Assistance to secure your dream career
  • Earn an ML Certification from IITM Pravartak (A Technology Innovation Hub of IIT Madras)
  • 24X7 Support for doubt resolutions & technical queries
In Collaboration With
08-Microsoft
IITM-Research

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Key Features

50+ Live sessions across 7 months
218 Hrs Self-paced Videos
200 Hrs Project & Exercises
Learn from IIT Madras Faculty & Industry Practitioners
1:1 with Industry Mentors
Resume Preparation and LinkedIn Profile Review
Campus Immersion at IITM Research Park
24/7 Support
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Machine Learning Course Overview

What skills will you master in this Machine Learning Course?

The course is designed by Industry professionals and IIT faculty 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.

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.

As a machine learning engineer, you will handle the end-to-end project lifecycle of a machine learning model, from collecting data to building a model, deploying it over the cloud, and evaluating it.

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Machine Learning engineers rank among the top emerging jobs. - LinkedIn
The global Machine Learning market is expected to reach USD 8.81 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% - MarketsandMarkets

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

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 jupyter Scipy numpy pandas matplotlib tensorflow SQL excel PowerBI
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Machine Learning Course Fees

Online Classroom Preferred

  • Everything in Self-Paced Learning, plus
  • 50+ Live sessions across 7 months of Instructor-led Training
  • One to one doubt resolution sessions
  • Attend as many batches as you want for Lifetime
  • Job Assistance
Weekend (Sat-Sun)

16 Nov 2024 08:00 PM - 11:00 PM
Weekend (Sat-Sun)

23 Nov 2024 08:00 PM - 11:00 PM
Weekend (Sat-Sun)

30 Nov 2024 08:00 PM - 11:00 PM
Weekend (Sat-Sun)

07 Dec 2024 08:00 PM - 11:00 PM
$1,229 10% OFF Expires in

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

IP ML - 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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Machine Learning Projects

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Machine Learning Certification

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About IIT Madras Pravartak Digital Skills Academy

IIT Madras Pravartak, a Technology Innovation Hub at IIT Madras, is funded by the Department of Science and Technology, Government of India, as part of the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS). The academy focuses on application-oriented research and innovation in the fields of SNACS. A significant achievement is BharOS, which was crafted and developed by a company incubated at IIT Madras Pravartak.

Key Achievements of IIT Madras:

  • In the NIRF 2024 rankings, IIT Madras was ranked No. 1 in the ‘Overall’ and ‘Engineering’ categories.
  • In the QS World Rankings 2024, IIT Madras is ranked No. 3 among Indian institutes and No. 227 internationally.
  • The Government of India has designated the title of ‘Institution of Eminence’ to IIT Madras.

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

  • Certificate from IIT Madras Pravartak.
  • Certificate from Microsoft in PowerBI.
  • Certificate from Microsoft in SQL.

These certificates will increase your credibility in machine learning, data visualisation and manipulation, giving you an edge.

There are a few requirements that need to be fulfilled to get this certificate:

  • Complete all the quiz on your LMS with at least 60% marks
  • Complete all the assignments and projects on your LMS and get them successfully evaluated by the respective faculty. A score of 60% or more is required to pass the evaluation.

After you have fulfilled all these requirements, you will be awarded the certificates.

More than 500 MNCs, including Sony, Infosys, Mu Sigma, Hexaware, Cisco, Standard Chartered Bank, Ericsson, and many others worldwide, recognise this machine learning course certification.

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Machine Learning Training FAQs

Why should I join this course at Intellipaat?

Here are a few reasons why you should consider enrolling in Intellipaat’s machine learning course, which is being offered in collaboration with IITM Pravartak.

  • 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 IIT faculty and best industry experts.
  • Earn an industry-recognised IITM Pravartak certificate.
  • Get 24*7 support to clear out your doubts.

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.

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.

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.

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 IIT faculty and 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.

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.

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