Assignments are listed by their due date.
| Week | Dates | Day and Topics | Assignments |
|---|---|---|---|
| 0 | Sep. 5-6 | Day 1: Introduction to course
Intelligence: What is it, where do we find it? | |
| Day 2: Constraint Satisfaction
Backtracking search | |||
| 1 | Sep. 9-13 | Day 3: Intelligence: How do we test it?
AI landscape, future directions of AI | BC: Computing Machinery and Intelligence summary |
| Day 4: Introduction to Neural Networks, Perceptron | BC: Constraint
Satisfaction/ Sudoku assignment | ||
| Day 5: Feed-forward networks, backpropagation | |||
| Day 6: Deep blue discussion, brute force solutions, pattern matching in chess | BC: Deep Blue summary | ||
| 2 | Sep. 16-20 | Day 7: Data set selection, OOD errors, GIGO, Introduction to NN assignment | |
| Day 8: Discussion of paper, Introduction to NN assignment cont'd, Data curation | BC: Great A.I. Awakening summary | ||
| Day 9: Ethics: Bias, Copyright issues, Hallucinations | |||
| Day 10: Introduction to Reinforcement Learning
Value Iteration | |||
| 3 | Sep. 23-27 | Day 11: Reinforcement Learning:
Markov Processes, Policy Iteration | BC: Cutting-edge work proposal |
| Day 12: Reinforcement Learning: Q-Learning
Monte Carlo Tree search | |||
| Day 13: Catch-up on RL | 23:59: FFNet assignment | ||
| Day 14: Quiz 1 | |||
| 4 | Sep. 30-Oct. 4 | Day 15: CNNs | |
| Day 16: CNNs continued, Introduction to CNN Assignment | |||
| Day 17: AlphaGoZero discussion, More on CNN Assignment | BC: AlphaGoZero summary | ||
| Day 18: Knowledge representation: Embeddings, Paraphrases, Ontologies, Common sense | |||
| 5 | Oct. 7-8 | Day 19: NLP, early work in NLP | |
| Day 20: Discussion of "What kind of Mind does ChatGPT have?" paper, RNNs | BC: What kind of Mind does ChatGPT have? summary | ||
| 6 | Oct. 14-18 | Day 21: AI at the pinnacle of science:
This year's Nobel prizes Hopfield Networks, RNNs and FFnets | |
| Day 22: LSTMs, Encoder-Decoder, Attention | |||
| Day 23: Reasoning in LLMs, Are NN intelligent? | 23:59: CNN - Milestone 1 | ||
| Day 24: Introduction to Transformers | |||
| 7 | Oct. 21-25 | Day 25: Quiz 2 | |
| Day 26: Transformers continued | |||
| Day 27: Research directions for the next break-through | |||
| Day 28: Cutting-edge work presentations | |||
| 8 | Oct. 28-Nov. 1 | Day 29: From Transformers to LLMs,
Pattern recognition, Discussion of Attention paper, AlphaFold | BC: Attention summary |
| Day 30: Human Computer Interaction,
AGI | |||
| Day 31: Backpropagation in CNNs. | |||
| Day 32: Cutting-edge work presentations | |||
| 9 | Nov. 4-8 | Day 33: Guest lecture by Eric Chen on "Developing large foundation models such as Meditron" | 23:59: Fine-tuning Llama assignment |
| Day 34: Impact of AI presentations | |||
| Day 35: Impact of AI presentations | |||
| Day 36: Cutting-edge work presentations | |||
| 10 | Nov. 11-15 | Day 37: Discussion of Dreyfus paper, Pattern recognition | BC: Alchemy and AI summary |
| Day 38: Quiz 3 | |||
| Day 39: Impact of AI presentations | 23:59: CNN - Milestone 2 | ||
| Day 40: Cutting-edge work presentations |