# Homework 2

The second homework assignment, posted on Github, is due on Monday, March 27 by 11:59pm ET.

Continue reading# Lecture 7: Regression, Part 2

This was the second lecture on the theory and practice of regression, focused on model complexity and generalization.

Continue reading# Lecture 6: Regression, Part 1

This was the first of two lectures on the theory and practice of regression.

Continue reading# Lecture 5: Data Visualization

We had a guest lecture from Çağatay Demiralp on data visualization.

Continue reading# Lecture 4: Counting at Scale

In this lecture we discussed combining and reshaping data in R as well as counting at scale with MapReduce.

Continue reading# Homework 1

The first homework assignment, posted on Github, is due on Thursday, February 23 by 11:59pm ET.

Continue reading# Lecture 3: Computational complexity

We had a guest lecture from Sid Sen on computational complexity and algorithm analysis.

Continue reading# Lecture 2: Introduction to Counting

Counting is surprisingly useful for understanding and summarizing social data. The key is figuring out what to count and how to count it efficiently.

Continue reading# Lecture 1: Overview

We used our first lecture to look at case studies in four main areas: exploratory data analysis, classification, regression, and working with network data.

Continue reading# Installing tools

This class will involve a good deal of coding, for which you will need some basic tools. Please make sure to set up the following tools after the first day of class.

Continue reading