Component
École Nationale Supérieure d'Électrotechnique d'Électronique d'Informatique d'Hydraulique et des Télécommunications
Objectives
- Understand the history of Artificial Intelligence (AI) and the reasons for its rise.
- Understand the different categories of AI, including machine learning and deep learning.
- Be aware of the limitations of AI and the challenges of development (particularly those related to databases).
- Understand different AI algorithms, along with their advantages and disadvantages.
- Develop a consistent and comprehensive database for the development of an embedded model (prepared in the previous semester).
Description
The course consists of 7 hours of lectures and 21 hours of project work. Assessment is based on a project report. The lectures present the concepts outlined in the learning objectives from a theoretical perspective. The project highlights the challenges of creating a database, even for a relatively simple application. It also provides hands-on experience with tools and hardware for developing embedded AI models on constrained hardware.
Pre-requisites
For the project, proficiency in C for embedded systems (µC) and Python is required.