Driven by recent breakthroughs, rapidly growing collections of data, and a plethora of exciting applications, artificial intelligence is experiencing massive interest and investment from both the academic and industrial scene.
This course selects a number of advanced topics to explore in machine learning and autonomous agents. Although these topics are diverse and extensive, this course is developed around a common thread connecting them all, such that each topic builds off the others.
Lectures will cover the relevant theory, and labs will familiarize the students with these topics from a practical point of view. Several of the lab assignments will be graded, and a team project on reinforcement learning will form a major component of the grade - where the goal is to develop and deploy an agent in an environment and write a report analyzing the results.
Grading: 50% for lab assignments + (40% + 10%) team project (team + individual component, respectively).
(There is no final exam)
- Teaching coordinator: Decock Jérémie
- Teaching coordinator: Elliker Clément
- Teaching coordinator: Loiseau Patrick
- Teaching coordinator: Read Jesse
- Teaching coordinator: Vanier Sonia