Anupam Rawat CV
← Academics

Education · 2023–27

IIT Madras

BS in Data Science and Applications, an online degree taken alongside IIT Bombay.

Selected courses. All 19 are listed under Academics.

Data science and ML

Machine Learning Foundations

The maths under machine learning: least squares, eigendecomposition, SVD and PCA, convex and constrained optimisation, and estimation with EM.

Machine Learning Techniques

PCA and kernel PCA, clustering, mixture models, regression with regularisation, classifiers from k-NN to SVMs, and boosting.

Machine Learning Practice

The same methods in scikit-learn, end to end, from data preparation to tuned models.

Introduction to Deep Learning and Generative AI

Neural networks, CNNs and sequence models, VAEs, GANs and diffusion models, and transformer language models, each with practice.

Tools in Data Science

Sourcing, cleaning, analysing and visualising data, and deploying the results.

Programming

Programming, Data Structures and Algorithms using Python

Complexity, sorting and searching, graphs, union-find, heaps and search trees, greedy, divide and conquer, dynamic programming and network flows.

Database Management Systems

SQL, relational design and normal forms, storage, indexing, transactions, recovery and query optimisation.

Modern Application Development I

Web applications end to end: HTML and CSS, models, controllers, REST APIs, security, testing and deployment.

Modern Application Development II

JavaScript and Vue front ends, state management, authentication, background jobs, messaging and performance.

System Commands (Linux shell)

Working in GNU/Linux: packages, shell variables and scripts, redirection, AWK and make.

Mathematics and statistics

Mathematics for Data Science II

Linear algebra from vector spaces to orthogonality, multivariable calculus and optimisation.

Statistics for Data Science II

Multiple random variables, estimation, Bayesian inference and hypothesis testing.

Business

Business Analytics

Regression, logistic regression and time series applied to business decisions.

Business Data Management

Economics, accounting and financial statements, selling and negotiation, worked through Excel case studies.