Schedule

The schedule below is a tentative outline of our plans for the semester.

Warning

This page is subject to change! Please check back frequently throughout the semester.

Before each class period, please watch the indicated videos and check your understanding by actively reviewing the associated Learning Goals and completing short Moodle checkpoint (CP) quizzes.

Readings refer to chapters/sections in the Introduction to Statistical Learning (ISLR) textbook (available online here). The ISLR readings are highly encouraged and serve as a nice complement to the videos and in-class activities.

All materials that you will need during class time (e.g., notes, activity templates) can be found on this website. You will access most assignments completed outside of class time (e.g. checkpoints, homework) via Moodle.

Week 1
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
1/23 Unit 0: Introductions \& Overview Information Gathering Survey Introductions
Complete CP1 before next class
Start HW0
ISLR\: Chap 1 \& Section 2.1 (skip 2.1.2-2.1.3)
Week 2
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
1/28 Unit 1: Model Evaluation Concept Video (script)
Checkpoint 1
Evaluating Regression Models
(QMD)
Complete CP2
Finish HW0
R Tutorial: Video (code)
ISLR: 2.2 (skip 2.2.3), 3.1
Concept Video: Evaluating Regression Models
R Tutorial Video: Introduction to TidyModels
1/30 Unit 1: Overfitting Checkpoint 2 Overfitting
(Part 1 QMD) (Part 2 QMD)
Complete CP3
Start HW1
R Tutorial: Video (code)
ISLR: 2.1.2, 5.1
Content Video: Overfitting
Week 3
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
2/4 Unit 1: Cross Validation Concept Video 1 (script)
Concept Video 2 (script)
Checkpoint 3
Cross-Validation
(QMD)
Complete CP4
Continue HW1
R Tutorial: Video (code)
ISLR: 5.1
Concept Video: Cross-Validation
R Tutorial: Training, Testing and Cross-Validation
2/6 Unit 2: Model Selection R Code Video (code)
Checkpoint 4
Model Selection
(Part 1 QMD)
(Part 2 QMD)
Complete CP5
Submit HW1
Start HW2
ISLR: 6.1
Concept Video: Model Building / Selection
R Tutorial Video: Preprocessing and Recipes
R Tutorial Video: Subset Selection
Week 4
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
2/11 Unit 2: LASSO (Shrinkage/ Regularization) Concept Video 1
Concept Video 2 (script)
Checkpoint 5
LASSO
(QMD)
Continue HW2 - ISLR: 6.2
- R tutorial: part 1& part 2 (code)
- LASSO (Shrinkage/ Regularization): Concept Video, R Tutorial
2/13 Unit 3: Nonparametric Models (see optional resources) Nonparametric Models
(QMD)
Finish HW2
Complete CP6
Start HW3
ISLR 2.1.2, 3.5
Week 5
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
2/18 Unit 3: KNN Regression and the Bias-Variance Tradeoff Concept Video 1 (script)
Concept Video 2 (script)
Checkpoint 6
KNN Regression
(QMD)
CP7
Continue HW3
- ISLR 2.2.2 (bias-variance), 3.5 (KNN)
- R code tutorial (code)
- KNN Regression and the Bias-Variance Tradeoff: Concept Video, R Tutorial
2/20 Unit 3: LOESS \& Splines Concept Video 1 Concept Video 2 (script)
Checkpoint 7
LOESS \& Splines
(QMD)
Continue HW3
Start Group Assign 1
- ISLR 7.1-7.4, 7.6-7.7
- Local Regression and GAMs: Concept Video, R Tutorial
- R Tutorial (splines)
Week 6
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
2/25 Units 1-3: Review Start Group Assignment 1 Regression Review \& Work Time - Finish HW3
- Study for Quiz 1
- Continue Group Assignment 1
2/27 MSCS CAPSTONE DAY (no class) Attend 2 MSCS capstone talks instead of class. Submit Capstone Reflections
Week 7
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
3/4 Units 1-3: Review Continue on Group Assignment 1 Work Time - Finish GA1
- Study for Quiz 1
- Start Learning Reflection 1
3/6 Quiz 1 (study!) Quiz 1 - CP8
- Continue Learning Reflection 1
Week 8
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
3/11 Unit 4: Classification via Logistic Regression Concept Video 1 (script)
Concept Video 2 (script)
Checkpoint 8
Logistic Regression
(QMD)
- Finish Learning Reflection
- CP9
- Start HW4
- Start Quiz Revisions
ISLR: 4.1-4.3
Concept Video: Logistic Regression
R Video: Logistic Regression
3/13 Unit 4: Evaluating Classification Models Concept Video 1 (script)
Concept Video 2 (script)
Checkpoint 9
Evaluating (binary) Classification Models
(QMD)
- Continue Quiz Revisions
- Finish HW4
ISLR: 4.1-4.3
Concept Video: Evaluating Classification Models
R Video: Evaluating Classification
Week 9
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
3/18 SPRING BREAK No Class
3/20 SPRING BREAK No Class
Week 10
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
3/25 Unit 5: KNN \& Decision Trees KNN \& Decision Trees
(QMD)
- Complete CP10
- Start HW5
ISLR: 2.2.3, 8.1
Concept Video: Decision Trees
R Video: Decision Trees
3/27 Unit 5: More KNN \& Decision Trees Concept Video 1 (script)
Concept Video 2 (script)
Checkpoint 10
More KNN \& Decision Trees
(QMD)
- Continue HW5 ISLR: 8.1
Concept Video: Decision Trees
R Video: Decision Trees
Week 11
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
4/1 Unit 5: Bagging and Random Forests Bagging \& Random Forests
(QMD)
- Complete CP11
- Continue HW5
- Finish activity
- Start Group Assignment 2
ISLR: 8.2
Concept Video: Bagging and Random Forests
R Video: Bagging and Random Forests
4/3 Units 4-5: Review Concept Video (script)
Checkpoint 11
Review GA2 Instructions
Units 4-5 Review - Finish HW5
- Continue GA2
- Study for Quiz 2
Week 12
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
4/8 Units 4-5: Review Work Day - Finish GA2
- Study for Quiz 2
- Start Learning Reflection 2
4/10 Units 4-5: Quiz (study!) Quiz 2 - CP12
- Continue Learning Reflection 2
Week 13
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
4/15 Unit 6: Hierarchical Clustering Concept Video 1 (script)
Concept Video 2 (script)
Checkpoint 12
Hierarchical Clustering
(QMD)
- Finish Learning Reflection 2
- CP13
- Start HW6
- Start Quiz 2 Revisions
ISLR: 12.4.2
Concept Video: Hierarchical Clustering
4/17 Unit 6: K-Means Clustering Concept Video (script)
Checkpoint 13
K-Means Clustering
(QMD)
- CP14
- Continue HW6
- Continue Quiz 2 Revisions
ISLR: 12.4.1
Concept Video: K-Means Clustering
Week 14
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
4/22 Unit 7: PCA Concept Video (script)
Checkpoint 14
Principal Component Analysis
(QMD)
- Submit HW6
- Continue HW7
- Finish Quiz 2 Revisions
ISLR: 12.2
Concept Video: PCA
4/24 Unit 7: PC Regression (bring Quiz Revisions to class!) Principal Component Regression
(QMD) + Work Time
- Finish HW7
- Continue GA3
- Study for Quiz 3
ISLR: 6.3.1
Week 15
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
4/29 Units 6-7: Review Review
+ Work Time
- Finish GA3
- Study for Quiz 3!
5/1 Units 6-7: Quiz (study!) Quiz 3 - Start Final Learning Reflection
Week 16
Date Topic Before Class: Videos/Readings In Class: Slides/Notes After Class: Assignments Additional Resources (Optional)
5/5-5/10 FINALS (no in-person meetings this week!) Submit Final Learning Reflection (due 5/10)