Slides and coding scripts are distributed after each lecture via the Google groups mailing-list. Refer to the home page on how to subscribe.
There are amazing resources available online, which the course will refer to, leverage and point at for delving into more details.
Aston Zhang, Zachary Lipton, Alexander J. Smola, Mu Li, 2023. Dive Into Deep Learning  (available at: https://d2l.ai/)
Francois Fleuret, 2024. The Little Book of Deep Learning. (available at: https://fleuret.org/dlc/)
Ian Goofellow, Yoshua Bengio, Aaron Courville, 2017. Deep Learning (available at: https://www.deeplearningbook.org/)
Frank Dellaert, 2024, Robotics. (available at: https://www.roboticsbook.org/)
Students are expected to have good knowledge of: 1) General notions of probability, mathematics, and algebra; 2) General notions of artificial intelligence and machine learning; 3) Familiarity with Python and Pytorch programming.