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E0 229: Foundations of Data Science

January--April 2014, Tue/Thu 2:00-3:30PM, Indian Institute of Science


(Feb 2) Please join the Course group here

(Feb 2) Students Crediting this course should fill this form

(Feb 2) Assignment 1 due on Thursday (Feb 6)

(April 4) Assignment 3 posted


Foundations of Data Science by John Hopcroft and Ravindran Kannan (text for the course)

Assignment 1

Assignment 3

Tentative Schedule

Here's a list of topics (these correspond to chapters in the book) along with the number of lectures we plan to devote to each topic. This is subject to change as the course progresses.

High-dimensional Space (Chap 2) 3 Ramesh

Singular Value Decomposition (Chap 4) 3 Ravi

Topic Models, Hidden Markov Process, Graphical Models, and Belief Propagation
 (Chap 9) 4 Ravi

Random walks (Chap 5) 3 Ramesh

Algorithms for Massive Data Problems (Chap 7) 6 Navin

Clustering (Chap 8) 4 Ravi

Learning and VC-dimension (Chap 6) 5 Navin



Navin Goyal <navingo at microsoft dot com>

Ramesh Hariharan <first name at strandls dot com>

Ravi Kannan <last name at microsoft dot com>


Achintya Kundu <achintya at csa dot iisc dot ernet dot in>

Chandrashekar Narayanan <chandrurec5 at gmail dot com>