Artificial intelligence is about the construction and study of systems that can automatically learn from data. With the emergence of massive datasets commonly encountered today, the need for powerful machine learning is of acute importance. Examples of successful applications include effective web search, anti-spam software, computer vision, robotics, practical speech recognition, and a deeper understanding of the human genome.
This course gives an introduction to this exciting field. In the first part, we will introduce basic machine learning techniques. The second part will focus on symbolic AI and the third part will introduce Deep Learning methods.
TBD
Lectures are scheduled from 8:00 to 9:30 on Fridays (most in room H202 of Ensimag), and practical session from 9:45 to 11:15 (most in rooms E100 and E101 of Ensimag) (iCal).
| # | Date | Room | Teacher | Topic |
|---|---|---|---|---|
| 1 | 03/02/2023 | H202 - E100 | PG/MA | Introduction to Artificial Intelligence (TP) |
| 2 | 10/02/2023 | H202 - E100/E101 | PG/MA | Unsupervised Learning (TP) |
| 3 | 24/02/2023 | H202 - E100/E101 | PG/MA | Supervised Learning (TP) |
| 4 | 03/03/2023 | H202 - E100/E101 | PG/MA | Regularization (TP) |
| 5 | 10/03/2023 | TBD | MCLR | Symbolic AI (1) |
| 6 | 17/03/2023 | H202 - E100/E101 | MCLR | Symbolic AI (2) |
| 7 | 24/03/2023 | H202 - E100/E101 | MCLR | Symbolic AI (3) |
| 8 | 31/03/2023 | TBD | PG | Deep Learning (1) |
| 9 | 07/04/2023 | H202 - E100/E101 | PG/MA/JSF | Deep Learning (2) (TP) |
| 10 | 21/04/2023 | H202 | MA/JSF | Deep Learning (TP) |
| 11 | 28/04/2023 | H202 | PG/MCLR | Revision |
| # | Btw May 2 and May 15 | Exam |
Contact: Marie-Christine.Rousset"at"imag.fr and pierre.gaillard"at"inria.fr
