PG Level Advanced Certification Programme in Applied Data Science and
Machine Learning

By IIT Madras, #1 in Engineering in India

IIT Madras data science and machine learning course is a comprehensive program designed to equip learners with in-demand skills and expertise in the field.

  • Talentsprint

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Data Science Course
  • #1 in Engineering in India, NIRF Rankings 2023
  • 12 Months
    PG Level program
  • 2Days at
    IITM Campus
  • 250+ HoursLive Interactive Classes & Hands-On Projects

3 Reasons Why This Programme is Unique

1 The IIT Madras Advantage

  • Designed by RBCDSAI at IIT Madras, India’s #1 ranked institution by NIRF in Engineering
  • Taught by top researchers in Applied Data Science and Machine Intelligence
  • Certification from the CODE (Center for Outreach and Digital Education) at IIT Madras

2Cutting-edge Applied Learning

  • Hands-on curriculum with use cases, capstones for effective learning
  • Visit IITM Campus** and practise at RBCDSAI, India's top Applied Research Lab
  • Industry interaction with experienced professionals

3 The TalentSprint Advantage

  • Learn on TalentSprint’s patent-pending Digital Platform
  • Network with 3000+ TalentSprint Deep Tech Alumni
  • Get Dedicated Support for Enhanced Career Outcomes

+91-9059896319 / Whatsapp

Hear from our program alumni

Find out why professionals want to join the programme

  • Data Science will create 11.5 Million
    job openings by 2026.
  • AI early career professionals
    command up to ₹20 LPA.

Top Data Science Job Profiles in India

  • Data Scientist
  • Data Science Manager
  • Machine Learning Engineer
  • Data Engineer
  • AI/ML Developer
  • AI Programmer
  • Junior Data Scientist
  • Junior Data Science Engineer
  • Data Analyst
  • Applied AI/ML Analyst
  • Backend AI Engineer
  • and more..

About IIT Madras

Indian Institute of Technology Madras (IIT Madras) is globally recognized for excellence in technical education, basic and applied research, innovation, entrepreneurship and industrial consultancy. Founded in 1959 with technical and financial assistance from the former government of West Germany, IIT Madras has been the top-ranked engineering institute in India for four consecutive years as well as the ‘Best Educational Institution’ in Overall Category in the NIRF Rankings by the Ministry of Human Resource Development. For more information visit

The PG Level Advanced Certification Programme in Applied Data Science and Machine Learning course will be delivered by the Robert Bosch Centre for Data Science and AI (RBCDSAI), one of India's pre-eminent interdisciplinary research centres for Data Science and AI with the largest network analytics, deep reinforcement learning, and the most active natural language processing and deep learning groups. The Centre was started to expand AI adoption in engineering applications and leverage the available expertise on network systems modelling across various Institute departments. The programme Certification will be awarded by the CODE (Center for Outreach and Digital Education) , IIT Madras that is committed to helping build national capabilities in science, technology, humanities, management, education and research.

  • #50 World University Ranking (Asia)
  • #1 in Engineering in India, NIRF Rankings 2023
  • #1 Atal Rankings of Institutions on Innovation Achievements, GoI

Data Science and Machine Learning
Course Overview

The 12-month online PG Level Advanced Certification Programme in Applied Data Science and Machine Learning, offered in partnership with the Robert Bosch Centre for Data Science and AI (RBCDSAI) at IIT Madras, is a cutting-edge course designed to enable learners to build deep tech capabilities and make data-driven business decisions. With the massive amount of data generated daily from millions of devices, Applied Data Science has become a crucial field in today's world. The program offers a unique learning experience that combines masterclass lectures, hands-on labs, hackathons, workshops, industry interactions, and a campus visit to fast-track learning.

The Data Science course covers various topics such as data preprocessing, machine learning algorithms, deep learning models, and natural language processing, among others, to prepare learners to handle complex data sets and provide data-driven solutions. The curriculum is designed to meet industry standards and includes real-world case studies, ensuring learners have hands-on experience working with industry-relevant tools and technologies. The course also enables learners to acquire soft skills such as communication, teamwork, and leadership, which are essential for success in the workplace.

Participants of the course benefit from the expertise of leading faculty members and industry experts, who provide personalized guidance and mentorship throughout the course. Upon completion of the course, learners receive a PG Level Advanced Certification in Applied Data Science and Machine Learning from IIT Madras, which enhances their career prospects and enables them to become sought-after professionals in the data science and machine learning field.

IITM Campus Visit

Data Science and Machine Learning Course Curriculum

Linear equations and solutions Matrices and their Properties; Eigenvalues and eigenvectors; Matrix Factorizations; Inner products; Distance measures; Projections; Notion of hyperplanes; halfplanes.

Probability theory and axioms; Random variables; Probability distributions and density functions ;Expectations and moments; Covariance and correlation; Statistics and sampling distributions; Hypothesis testing of means, proportions, variances and correlations; Confidence intervals; Correlation functions; Parameter estimation – MLE and Bayesian methods

Unconstrained optimization; Necessary and Sufficiency conditions for optima; Gradient descent methods; constrained optimization, KKTConditions; Introduction to least squares optimization;

1. Use cases from the healthcare domain where NLP is applied

  • a. Automatic case-correction of all-caps or all-small text from EMRs.
  • b. Automatic token splitting of conjoined words and sentences.
  • c. NER on EHRs
  • d. Table detection and extraction of EOBs and EHRs.
  • e. Computer-assisted medical coding of EHRs.

2. Models such as Bi-LSTM-CRF, CAML, HAN, ResNexT.

3. Public domain datasets - MIMIC-III.

Introduction to big data in biology

Levels of omics data, basic information flow in biology

Importance of Networks in Biology: Overview

Introduction to Network Science

Learning from Network structure: Predicting essential genes

Learning on Networks: Community detection to identify disease genes - Learning using Networks: Graph mining for predicting biosynthesis routes - Omic data analysis: Predicting mutations and genes that drive cancer

1. Problem Statement : Four case studies will be demonstrated. CS1: Choice of mode CS2: Travel time estimation CS3: Accident hot spot analysis CS4: Accident severity modelling

2. Model(s) intended to demonstrate : Logistics regression, Support vector regression, k-means clustering and random forest

3. Dataset to be used during the demo

4. Dataset for the mini project

1. Levels of omics data, basic information flow in biology

2. Genomics, Transcriptomics, Epigenomics, Proteomics and Multi omics - Identification human disease genes using genomics

3. Application of transcriptomics for identifying disease mechanisms

4. Clinical data - kinds of clinical data Garbhini dataset - a clinical data case study

a. Artificial Neuron

b. Multilayer Perceptron

c. Universal Approximation Theorem

d. Backpropagation in MLPs

e. Backprop on general graphs

a. Gradient Descent and its variants

b. Momentum, Adam, etc.

c. Batch Normalization

a. Introduction

b. CNN Operations

c. CNN Training

d. Illustrative Example (“Hello World”) - MNIST digit classification e. Image Recognition-SoTA model(s)

f. Object detection/localization - SoTA model(s)

g. Semantic segmentation -SoTA model(s)

a. Smart Cities

b. Industry Use case 1

c. Climate Science

d. Manufacturing

e. Bio-informatics

Industry Use case 2

Tools covered

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Capstone Projects

  • Recommendation Systems
  • Object Recognition System
  • Digit Recognition System
  • Financial Fraud Detection System
  • Anomaly Detection in Manufacturing Systems
  • Urban Infrastructure Analytics
  • Healthcare Analytics
  • And more


The programme is designed by a distinguished faculty group bearing academic accreditation from premier institutions around the world.

Dr. Arun Rajkumar

Ph.D., Computer Science and Automation, IISc

Machine Learning, Rank Aggregation, Statistical Learning, Sequential Decision Making

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Dr. Balaraman Ravindran

Ph.D., Computer Science, University of Massachusetts, Amherst, USA

Reinforcement Learning, Geometric Deep Learning, Data Mining

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Dr. Nandan Sudarsanam

Ph.D., Engineering Systems, MIT, Cambridge, MA, USA

Experimentation, Applied Statistics and Machine Learning

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Dr. Nirav P. Bhatt

Ph.D., Computer, Communication and Information Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland

Machine Learning for Biological and Engineering Networks, Safe Reinforcement Learning

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Dr. Karthik Raman

Ph. D., Systems Biology, IISc

Biological Networks, Computational Systems Biology, Genomics and Computational Biology

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Dr. Gitakrishnan Ramadurai

Ph.D., Transportation Engineering, Rensselaer Polytechnic Institute, NY, USA

Dynamic Traffic Assignment, Transportation Network Modelling, Intelligent Transportation Systems, Pedestrian Safety

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Participant Profile


Our Alumni Work with Top Organizations

All logos belongs to respective companies

Delivery Format

  • Faculty-led Interactive Masterclass Lectures
  • Hands-on Labs
  • Mentor Support
  • Hackathons
  • Workshops
  • Interactions with Experienced Professionals
  • 1 Campus Visit of 3 Days towards the end of the cohort**

**Dates will be decided keeping the safety of participants in mind. Fees will be based on actuals.


  • Education: B.E./M.E./B.Tech/M.Tech/B.Sc./M.Sc or an equivalent degree
  • Work Experience: Minimum 1 Year
  • Coding Experience: Basic Programming Knowledge Required

Admission Process

    Apply for the Programme

    Wait for Selection

    Block Your Seat

    Enroll for the Programme

    Start Building Expertise

    Get Certified by CODE, IIT Madras

    The selection for the programme will be done by IIT Madras and is strictly based on the eligibility criteria and the motivation of applicants as expressed in their statement of purpose.

Class Start - April 2024

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What is My Investment?

Program Fee ₹2,50,000 (18% GST as applicable)

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Application Fee ₹2,000

Special Pricing for Corporates

Campus visit fee to be borne by participants. Will be based on actuals.

Fees paid are non-refundable and non-transferable.

Modes of payment available

  • Internet Banking
  • Credit/Debit Card
  • UPI Payments

Easy Financing Options

12 Month 0% Interest Scheme / Interest-Based Schemes

EMI as low as ₹8,358/Month

EMI Options

Loan Partners

About TalentSprint

Frequently Asked Questions

It is well known that Data Science helps businesses extract actionable insights from massive sets of data. Data Science and the technologies empowering it, like AI and Machine Learning, have become central to every business strategy today.

However, Applied Data Science takes the game many notches higher. It broadens the scope of data science to include

  • Finding new applications where data science can be applied and
  • Create predictions that are more accurate in their trends and seasonality

Applied Data Science becomes important in the backdrop of the fact that the global data created per day is likely to reach 463 Billion GB/Per Day by 2025 from 44 Billion GB/Per Day in 2016 according to IDC. Such massive data cannot be made sense of by traditional algorithms.

This is where Machine Intelligence (MI) can add immense value to business in conjunction with Applied Data Science.

Machine Intelligence as a higher evolution of machine learning - a stepping stone to true AI.

According to LinkedIn, Applied Data Science and Machine Learning offers exciting job opportunities for professionals with expertise in these fields.

  • Data Scientist (7000+ openings)
  • Data Science Manager (2000+ openings)
  • Machine Learning Engineer (24,000+ openings)
  • Data Engineer (29,000+ openings)
  • AI/ML Developer (4000+ openings)
  • AI Programmer (8000+ openings)
  • Junior Data Scientist (1000+ openings)
  • Junior Data Science Engineer (1000+ openings)
  • Data Analyst (10,000+ openings)
  • Applied AI/ML Analyst (600+ openings)
  • Backend AI Engineer (980+ openings)

The IIT Madras Advantage

  • Designed by RBCDSAI at IIT Madras, India’s #1 ranked institution by NIRF in Engineering
  • Taught by top researchers in Applied Data Science and Machine Learning
  • Certification from the Center for Continuing Education at IIT Madras

Cutting-edge Applied Learning

  • Hands-on curriculum with use cases, capstones for effective learning
  • Visit the IIT Madras campus* and practise at RBCDSAI, India’s top Applied Research Lab

The TalentSprint Advantage

  • Learn on TalentSprint’s patent-pending Digital Platform
  • Network with 3000+ TalentSprint Deep Tech Alumni
  • Get Dedicated Support for Enhanced Career Outcomes

The programme will be delivered in an interactive online format, retaining effectiveness while maintaining safety. The format uniquely combines the benefits of an in-class programme with the flexibility and safety of online learning.

  • Synchronous programme delivery by expert faculty
  • Interact and get your doubts answered by faculty
  • Peer learning through working in groups with other participants
  • Get support from mentors for labs and experiments
  • Re-attend classes through recorded archives
  • Access videos easily with searchable and indexed video archives
  • Learn from the comfort and safety of your home
  • Office hours with one-on-one mentor support

The programme will be delivered on TalentSprint's patent-pending, a leading digital learning platform of choice used for programs delivered by the likes of Google, IIM Calcutta, IIT Hyderabad, IISc, and IIT Kanpur, to name a few.