Calendar

Topic
Module 0 - Introduction / Regression
Mon 03/31
LES 00 Regression
resources:
Extra resources
Tue 04/01
Wed 04/02
LES 01 Assessing Performance; Bias + Variance Tradeoff
Thu 04/03
SEC 00 Course Infrastructure; Pandas
Fri 04/04
Module 1 - Assessing Performance
Mon 04/07
LES 02 Regularization: Ridge
Tue 04/08
Wed 04/09
LES 03 Regularization: LASSO, Feature selection
Thu 04/10
SEC 01 Ridge and LASSO; Code
Fri 04/11
Module 2 - Classification
Mon 04/14
LES 04 Classification
Tue 04/15
Wed 04/16
LES 05 MLE / Logistic Regression
Thu 04/17
SEC 01 Classification ; Logistic Regression
Fri 04/18
Module 3 - Societal Impact, Bias, and Fairness
Mon 04/21
LES 06 Bias and Fairness
Tue 04/22
Wed 04/23
LES 07 Fairness and Tradeoffs ; Recap
Advanced resources
Thu 04/24
SEC 02 Midterm Review
Fri 04/25
Module 4 - Trees/Ensemble Methods
Mon 04/28
LES 08 Naive Bayes / Decision Trees
Tue 04/29
Wed 04/30
LES 09 Ensemble Methods
Thu 05/01
SEC 03 Trees and Ensemble Methods
Fri 05/02
Module 5 - Deep Learning
Mon 05/05
LES 10 Neural Networks
Tue 05/06
Wed 05/07
LES 11 Deep Learning; Convolutional Neural Networks
Thu 05/08
SEC 04 Deep Learning
Fri 05/09
Module 6 - Non-Parametric Methods
Mon 05/12
LES 12 Precision + Recall / kNN
Tue 05/13
Wed 05/14
LES 13 Kernel Methods; Locality Sensitive Hashing
Thu 05/15
SEC 05 Kaggle Setup
Fri 05/16
Module 7 - Clustering
Mon 05/19
LES 14 Clustering
Tue 05/20
Wed 05/21
LES 15 Hierarchical Clustering
Thu 05/22
SEC 06 Numpy ; Variable Encoding ; Clustering
Fri 05/23
Module 8 - Recommender Systems
Mon 05/26
HOLIDAY Memorial Day
Tue 05/27
Wed 05/28
LES 16 PCA / Recommender Systems Intro
Thu 05/29
SEC 07 PCA ; Recommender Systems
Fri 05/30
Module 9 - Course Wrap Up
Mon 06/02
LES 17 Recommender Systems / Matrix Factorization
Tue 06/03
Wed 06/04
LES 18 Course Wrap Up; Next Steps; Generative AI
Fri 06/06
Module 10 - Finals Week
Mon 06/09
Tue 06/10
Wed 06/11