Diploma in Data Science 

offered by IIT Madras

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

Machine Learning Techniques

Introduction; Unsupervised Learning - Representation learning - PCA

Unsupervised Learning - Representation learning - Kernel PCA

Unsupervised Learning - Clustering - K-means/Kernel K-means

Machine Learning Practice

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

Graph Theory(VOL 3)

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

Tools in Data Science

Everyday tools

Data sourcing

Data preparation

Data analysis