Schedule
Lecture and tutorial plan with slides and suggested readings.
Lectures
This is a tentative schedule and may change as the course proceeds. Check Piazza and Canvas for updates.
| Lectures | Dates | Topic | Notes |
|---|---|---|---|
| Week 1 | Jan. 5 - Jan. 9 | What is Intelligence ? ; Feasibility of Learning | Notes 1 Slides |
| Week 2 | Jan. 12 - Jan. 16 | Feasibility of Learning (contd) : Generalization Bounds and VC dimension | Notes 2 |
| Week 3 | Jan. 19 - Jan. 23 | Perceptron and Stochastic Gradient Descent Assignment - 1 released (Jan 19) | Notes 3 |
| Week 4 | Jan. 26 - Jan. 30 | Kernels and Beginnings of Neural Networks Assignment - 1 due (Feb 1) | Notes 4 |
| Week 5 | Feb. 2 - Feb. 6 | Deep Fully Connected Networks and Backpropagation Assignment - 2 released (Feb 2) | Notes 5 |
| Week 6 | Feb. 9 - Feb. 13 | Convolutional Neural Networks | Notes 6 |
| Term Break | Feb. 16 - Feb 20 | ||
| Week 7 | Feb. 23 - Feb. 27 | Classification Loss Function, and Practical ML : Validation, Hyperparameters Assignment - 2 due (March 1) | Notes 7-8 |
| Week 8 | Mar. 2 - Mar. 6 | MidTerm Quiz (~ March 2nd) Regression and Regularization | Notes 9 |
| Week 9 | Mar. 9 - Mar. 13 | Optimization, Convexity, Gradient Descent Assignment - 3 released (Mar 9) | Notes 10 |
| Week 10 | Mar. 16 - Mar. 20 | Convergence Rate for Gradient Descent and Accelerated Gradient Descent (Momentum) Course Project Proposal due (Mar 20) | |
| Week 11 | Mar. 23 - Mar. 27 | PCA, Clustering, Decision Trees Assignment - 3 due (Mar 22) | Notes 11 |
| Week 12 | Mar. 30 - Apr. 3 | Introduction to Reinforcement Learning, Deep Q Networks Assignment - 4 released (Mar 30) No lecture on April 3rd, 2026 (Good Friday) | Notes 12 |
| Week 13 | Apr. 6 - Apr. 10 | No lecture on April 6th, 2026 (Easter Monday) Policy Gradient Methods, Sequence Models Assignment - 4 due (Apr 12) | |
| Course Project Report | Due April 15 |
Tutorials
2:00 pm - 3:00 pm Fri., MCLD 3002
| Tutorials | Dates | Topic | Slides | Suggested Readings |
|---|---|---|---|---|
| Jan. 5 - Jan. 9 | No tutorials on Week 1 | |||
| Jan. 12 - Jan. 16 | No tutorials on Week 2 | |||
| Jan. 19 - Jan. 23 | Tutorial on prototype based classifier for Assignment-1, Anthony Cheng | |||
| Jan. 26 - Jan. 30 | No tutorials, but TA Beidi Zhao will be present after class to help with Assignment-1 | |||
| Feb. 2 - Feb. 6 | Tutorial on PyTorch for Assignment-2, Anthony Cheng | code | ||
| Feb. 9 - Feb. 13 | Tutorial on CNN training for Assignment-2, Beidi Zhao | |||
| Feb. 23 - Feb. 27 | No tutorials, but TA Beidi Zhao will be present after class to help with Assignment-2 |