Schedule
Lecture slides and Jupyter notebooks can be found here.
| Lecture 1 | Jan. 27 | overview, simple perceptrons |
| Lecture 2 | Jan. 29 | stochastic gradient descent |
| Pset 0 | Jan. 31 | math review |
| Lecture 3 | Feb. 3 | multilayer perceptrons |
| Lecture 4 | Feb. 5 | convolution |
| Pset 1 due | Feb. 7 | perceptrons |
| Lecture 5 | Feb. 10 | convolutional nets |
| Lecture 6 | Feb. 12 | visual object recognition |
| Pset 2 due | Feb. 14 | MLPs and convolution |
| Exam 1 | Feb. 17 | |
| Lecture 7 | Feb. 19 | generalization & regularization |
| Lecture 8 | Feb. 24 | BatchNorm, transfer learning |
| Lecture 9 | Feb. 26 | object detection |
| Pset 3 due | Feb. 28 | convolutional nets |
| Lecture 10 | Mar. 3 | deconvolution layers |
| Lecture 11 | Mar. 5 | segmentation |
| Pset 4 due | Mar. 7 | segmentation and denoising |
| Break | ||
| Lecture 12 | Mar. 17 | autoencoders and diffusion models |
| Lecture 13 | Mar. 19 | language models and attention |
| Pset 5 due | Mar. 23 | diffusion models |
| Lecture 14 | Mar. 24 | transformers |
| Lecture 15 | Mar. 26 | pretraining/GPT |
| Pset 6 due | Mar. 30 | transformers 1 |
| Lecture 16 | Mar. 31 | deep RL |
| Lecture 17 | Apr. 2 | posttraining/SFT/RLHF |
| Exam 2 | Apr. 7 | Exam 2 |
| Lecture 18 | Apr. 9 | AlphaGo |
| Project | Apr. 11 | proposal v1 due |
| Lecture 20 | Apr. 14 | project meetings |
| Lecture 21 | Apr. 16 | agents and tool use |
| Project | Apr. 18 | proposal v2 and status report |
| Lecture 22 | Apr. 21 | project meetings |
| Lecture 23 | Apr. 23 | AI safety |
| Reading period | Apr. 30 | project oral presentations |
| Final project | May 10, 8:30am | project papers due |