PAIA
Perspectives in Learning and Artificial Intelligence
Description: This module offers insight into real-world applications of machine learning through talks by researchers and industry professionals. Each session highlights a specific application domain (healthcare, finance, energy, robotics, etc.), illustrating how classical or advanced techniques are used to address real-world problems. These talks complement academic instruction by exposing students to more advanced approaches at times, thereby fostering a broader understanding of current challenges and practices in professional or research settings.
Learning outcomes: At the end of this module, students will have gained a broad perspective on real-world applications of machine learning across various sectors. They will be able to analyze real-world problems through the lens of AI, understand the methodological choices made by experts, and identify the specific constraints related to implementing solutions in industrial or research contexts. This module will also enhance their ability to engage in dialogue with professionals in the field and to envision themselves contributing to interdisciplinary projects involving machine learning.
Means: Each module (5 in total) is given by an industrialist or a researcher. It consists of a 1h30 lecture followed by a 3h practical session.
Evaluation methods: At the end of each practical session, a submission will be required by the instructor. One submission will then be randomly selected for evaluation by the instructor. The grade given will serve as the assessment for the entire module.
Evaluated skills:
- Be operational, responsible, and innovative in the digital world
Course supervisor:
- Joël Legrand
Geode ID: 3MD4110
