Schedule

This page contains an outline of the topics, content, and assignments for the semester. Note that this schedule will be updated as the semester progresses.

We will have meetups on XXX evenings at X:00pm.

Meetups will be recorded and made available the next day on the course website. Although attending live is not strictly required, I expect everyone to watch the lectures during the week. I use the class meetups to convey important information and announcements. Very often I will cover some topics not in the textbook. Students who attend the meetups tend to do well on the assignments.

Week	Start	End	Meetup	Topic	Prepare	Lab	Slides	Video	Resources
1				Introduction to the course
2				Introduction to Modeling
3				Linear regression
4				Multiple regression
5				Maximum Likelihood Estimation and Logistic Regression
6				Generative Models for Classification
7				Resampling Methods
8				Tree Based Methods
9				Bagging and Random Forests
10				Support Vector Machines
11				Principal Component Analysis
12				Clustering Methods
13				Missing data
14				Bayesian Analysis
15				Wrap up / Final Presentations