| Topic | Lecture # | Teacher | Sub-topic | Date | Time |
|---|---|---|---|---|---|
| Symbolic AI | Lecture 1 | Emiliano Lorini | Symbolic AI: History and Foundations | March 28 | 5-7pm |
| Neural Networks | Lecture 2 | Aimen Zerroug | Neural Networks: History and Foundations | March 29 | 5-7pm |
| Computer Vision | Lecture 3 | Mohit Vaishnav | Image classification | April 4 | 5-7pm |
| Computer Vision | Lecture 4 | Benjamin Devillers | Unsupervised/zero/few-shot learning | April 7 | 5-7:30pm |
| Computer Vision | Lecture 5 | Colin Decourt | Object detection, segmentation | April 12 | 5-7pm |
| NLP | Lecture 6 | Chloe Braud | Natural Language Processing basics | April 14 | 5-7pm |
| NLP | Lecture 7 | Romain Bielawski | Recurrent Neural Networks for NLP | April 19 | 5-7pm |
| NLP | Lecture 8 | Romain Bielawski | Attention/Transformers in NLP | April 21 | 5-7pm |
| Computer Vision | Lecture 9 | Mohit Vaishnav | Visual Reasoning | April 28 | 5-7pm |
| Audio | Lecture 10 | Ismail Khalfaoui | Sound processing, speech recognition | May 5 | 5-7pm |
| DL/Neuro | Lecture 11 | Rufin VanRullen | Homologies between brain & CNNs | May 9 | 5-7pm |
| DL/Neuro | Lecture 12a | Javier Cuadrado | Spiking neural networks | May 12 | 5-6pm |
| DL/Neuro | Lecture 12b | Leila Reddy | Brain decoding with Machine Learning | May 12 | 6-7pm |