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
| |