Syllabus

Below is a tentative outline of course lectures, subject to change.

Date Topic
January 25 Introduction: Case Studies in Computational Social Science
February 1 Counting: An Introduction
February 8 Counting at Scale: MapReduce, Part I
February 15 Counting at Scale: MapReduce, Part II
February 22 Networks and Diffusion: Theory
March 1 Networks and Diffusion: Case studies
March 8 Complexity of Counting, Part I
March 15 Complexity of Counting, Part II
March 22 Spring Break
March 29 Data Wrangling
April 5 Online Experiments
April 12 Regression: Case Studies
April 19 Regression: Theory and Practice
April 26 Classification: Theory and Practice
May 3 Student Presentations