Day	Lecture	Demo	Discussion	Due	Reading
M April 3	Introduction		(Optional) Discussion 0
W April 5	Visualization	sales	Discussion 1		Pandas tutorials
M April 10	Munging	fires join			Helpful functions
W April 12	Models and inference	inference	Discussion 2 team formation
F April 14				hw1 census data project groups
M April 17	CLT and confidence intervals	inference
W April 19	Bootstrap	bootstrap	Discussion 3	hw2
M April 24	Hypothesis tests	testing			Data 8 ch11
W April 26	Correlation	correlation	Discussion 4		Data8 ch 15.1
Th April 27				hw3
F April 28				project proposal
M May 1	Linear regression	regression		Quiz 2
T May 2				hw4
W May 3	CI for regression	regression uncertainty, electricity	Discussion 5
M May 8	Feature generation	crime
T May 9				hw5
W May 10	Model selection	crime	Discussion 6
F May 12				project midterm report
M May 15	More feature generation
T May 16				hw6
W May 17	More feature generation	crime
M May 22	Logistic regression
T May 23
W May 24	Error metrics		Discussion 7
F May 26				Quiz 4
M May 29	Holiday			hw7
T May 30
W May 31	Forecasting	forecasting	Discussion 8
M June 5	Causal inference			hw8
W June 7	AutoML			Quiz 5
F June 9				project final report and peer evaluations (extended to June 11)