Schedule

Note: The timeline of topics and assignments might be updated throughout the semester.

week	date	topic	slides	appex	assignment	assessment	prepare
1	9 January	Welcome
1	11 January	Lab 01: Welcome to R
2	16 January	MLK [No Class]
2	18 January	Trade-offs: Accuracy and interpretability, bias and variance
3	23 January	Design Principles of Data Analysis
3	23 January	Data Visualization in R
3	23 January	Exploratory Data Analysis
3	25 January	Cross-validation
4	30 January	Introduction to tidymodels
4	1 February	Lab 02: Cross-validation
5	6 February	Introduction to Linear Regression
5	8 February	Linear Regression in R
6	13 February	Logistic Regression
6	15 February	Lab 03: Logistic Regression
6	20 February	Lab 03: Logistic Regression
6	22 February	Ridge Regression
7	27 February	Lasso & Elastic Net
7	27 February	Penalized Regression in R
7	1 March	Lab 04: Ridge, Lasso, Elastic Net
	6 March	Spring Break [No Class]
	8 March	Spring Break [No Class]
9	13 March	Missing Data
9	15 March	Review
10	20 March	Midterm
10	22 March	[Midterm Part 2: Take Home NO CLASS]
11	27 March	Polynomial Regression and Splines
11	29 March	Non-linear Models in R
11	29 March	Lab 05: Non-linear models
12	3 April	Decision Trees (Regression)
12	5 April	Decision Trees
12	5 April	Decision Trees (Classification)
12	10 April	Bagging
13	10 April	Random Forests
13	10 April	Boosted Decision Trees
13	12 April	Neural Networks
14	17 April	Lab 06: Ensemble Models
14	19 April	Lab 06: Ensemble Models
15	24 April	Communicating with Statistics
15	26 April	Honesty in Statistics and Trust in Experts