Diploma in Data Science
offered by IIT Madras

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Public/Government Institute
Estd. 1959

Diploma in Data Science
at
IIT Madras
Overview

Learn to represent sets and relations between set elements as discrete graphs using nodes and edges

Duration	12 months
Total fee	₹55,000
Mode of learning	Online
Course Level	UG Diploma

Diploma in Data Science
at
IIT Madras
Highlights

Earn a Diploma of completion from IIT Madras
One or more weekly online assignments
Three quizzes will be conducted at the end of Weeks

Diploma in Data Science
at
IIT Madras
Course details

Skills you will learn

Data Modeling Business Analytics Regression Python Data Science

What are the course deliverables?

Identifying failure modes
Working with large data sets
Build data-centric business models

More about this course

The Diploma in Data Science exposes the learner to the holistic approach of gathering, analysing, and interpreting data for a variety of problems
The courses on Business Data lays down the context and the need for the data, while the Machine Learning courses equip the learner to use and analyse this data towards impactful conclusions
This course lays the groundwork for the upcoming ML courses by covering various fundamentals that do not necessarily fall under Machine Learning but are quite necessary for a comprehensive understanding of Machine Learning
This course provides a basic understanding of how businesses are organised and run from a data perspective
This theory course introduces the main methods and models used in machine learning problems of regression, classification and clustering
This companion course to the ML Theory course introduces the student to scikit-learn, a popular Python machine learning module, to provide hands-on problem solving experience for all the methods and models learnt in the Theory course

Diploma in Data Science
at
IIT Madras
Curriculum

Machine Learning Foundations

Introduction to machine learning

Calculus

Linear Algebra - Least Squares Regression

Linear Algebra - Eigenvalues and eigenvectors

Business Data Management

Consumption and demand: Micro & Macro economics: the role of data, production, consumption and exchange, consumption baskets, sources of consumer survey data

Micro-economic concepts: Utility: cardinal vs ordinal, indifference curves. Demand and supply curves, changes in demand and elasticity. production cost, cost curves. Make vs buy decisions, production quantity decisions

Firm level strategies and performance data: Objectives and types of pricing strategies, analysis of firm performance - key ratios. Analysis examples: Ultratech, Page Industries, Nestle, TCS

Analysing industry level data: Industry definition and classification codes, IIP and PMI, industry market structure and concentration indices, competitive positioning in an industry - Porter's five forces. Analysis examples: Cement industry, Textile industry, FMCG industry, IT industry

Machine Learning Theory

Introduction to machine learning

Models of regression

Models of classification

Nearest Neighbours - regression and classification problems

Support Vector Machines

Decision Trees, Ensemble Methods and Random Forests

Machine Learning Practice

End-to-end machine learning project on scikit-learn

End-to-end machine learning project on scikit-learn (Continued)

Regression on scikit-learn - Linear regression Gradient descent - batch and stochastic.

Polynomial regression, Regularized models

Business Analytics

Data dashboarding Insights from data summary

Can summarizing the data provide insights?

Do people in different cities prefer different brand?

Predicting the stock returns -Regression basics

Tools in Data Science

Discover the problem

Get the data

Prepare the data

Model the data

Diploma in Data Science
at
IIT Madras
Faculty details

Ashish Tendulkar

ExperiencDr. Ashish Tendulkar is a researcher with Google Research Bangalore. He holds Masters and PhD from IIT Bombay. Before his current position, he was an Assistant Professor at IIT Madras and Head of data sciences at Persistent Systems Pune.ed Associate Professor with a demonstrated history of working in the higher education industry. Skilled in Mathematical Modeling, R, Stochastic Modeling, and Statistical Modeling.

S Anand

Anand is a co-founder of Gramener, a data science company. He leads a team that tells visual stories from data. He is recognized as one of India’s top 10 scientists, and is a regular TEDx speaker.

Prashanth LA

Prashanth L.A. is an Assistant Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Madras. Prior to this, he was a postdoctoral researcher at the Institute for Systems Research, University of Maryland - College Park from 2015 to 2017 and at INRIA Lille - Team SequeL from 2012 to 2014.

G Venkatesh

Dr. Venkatesh is a Professor of Practice at IIT Madras, where he is involved with several projects in the field of education. He is also a Fellow and Director of Sasken Communication Technologies Ltd, a leading Indian R&D services provider, and a founder of Mylspot, an education technology startup that aims to bridge knowledge gaps of students through a mentored learning platform.