CS2109S AY 2025/26 Semester 2
Tutorial Slides (T42) Show Week 1-6
Tutorials start in Week 3.
Tutorial slides will be released after each tutorial session.
Please do not share the slides with other classes before all tutorial classes in the week are over.
Feel free to contact me if you spot any errors in the materials.
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| Week # | Tut # | Date | Topics | Slides | Recording | Other Notes | |
|---|---|---|---|---|---|---|---|
| 2 |
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| 3 | 1 | 29 Jan |
Uninformed Search Informed Search Problem Set 1 due: 31 Jan, 23:59 |
post | live | link | Bonus Lab 1: Leveling Up in NumPy | |
| 4 | 2 | 5 Feb |
Adversarial Search Local Search Problem Set 0 due: 7 Feb, 23:59 |
post | live | link |
Bonus Lab 2:
A Good Local Search
Solution to Bonus Question |
|
| 5 | 3 | 12 Feb |
Decision Trees Linear Regression Problem Set 2 due: 14 Feb, 23:59 |
post | live | link |
Bonus Lab 3:
Learning Rate Schedulers
Important: Gradient Descent Recording Matrix Calculus Cheatsheet |
|
| 6 | 4 | 19 Feb | Classification and Logistic Regression
Zoom Tutorial Join Zoom Meeting |
post | live | link | Bonus Lab 4: Exploring Softmax Func. | |
| R |
Practice Midterms: 21/22 Sem 2 (Solutions) | 22/23 Sem 1 Solutions | 22/23 Sem 2 Solutions | 23/24 Sem 1 Solutions | 23/24 Sem 2 Solutions | 24/25 Sem 1 Solutions | 24/25 Sem 2 Solutions | 25/26 Sem 1 Solutions Practice Finals: 21/22 Sem 2 | 24/25 Sem 1 Context Questions & Solutions | 24/25 Sem 2 Questions & Solutions Response to Appeals | 25/26 Sem 1 Questions & Solutions Response to Appeals Notes: (1) Note on Syllabus (2) Where are the other past year finals?
The midterm used to cover ONLY lectures 1-4 (up to decision trees, not even linear regression). So you might want
to check out some of the past year finals for practice.
Please also note that the SVM and neural networks coverage has been revised - you might find some questions in the past finals out of syllabus (support vector machines, perceptron learning algorithm, etc.).
CS2109S is a relatively new course starting AY 21/22 Sem 2, and it has turned into a practical exam format in AY 22/23 and
AY 23/24 (if you heard about the infamous 2-hour practical exam / 28-hour take-home exam). I do have those papers, but they're
probably not useful for your exam preparation.
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| 7 |
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| 8 | 5 | 12 Mar |
Regularisation and Kernels
Problem Set 3 due: 14 Mar, 23:59 |
post | live | link | Bonus Lab 5: Composing Kernels | |
| 9 | 6 | 19 Mar |
Multi-Layer Perceptrons Back Propagation |
post | live | link | ||
| 10 | 7 | 26 Mar | Convolutional Neural Networks | post | live | link | Bonus Lab 6: Behind Pytorch Autograd | |
| 11 | 8 | -- |
Recurrent Neural Networks
Prerecorded Tutorial |
post | live | link | ||
| 12 | 9 | 9 Apr |
Attention Neural Networks
Problem Set 4 due: 11 Apr, 23:59 |
post | live | link | Bonus Lab 7: Messing with a GPT Model | |
| 13 | 10 | 16 Apr |
Unsupervised Learning with Neural Networks Review Capstone Project (10%) due: 17 Apr, 23:59 | post | live | link | ||
| R |
Good luck for your final exams! |
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Last updated: 16 April 2026