Intelligent systems: communications & AI
COM-304 / 8 crédits
Enseignant(s): Al Hassanieh Haitham, Roshan Zamir Amir
Langue: Anglais
Withdrawal: It is not allowed to withdraw from this subject after the registration deadline.
Summary
The course teaches the development of systems that solve real-world challenges in communications, signal processing, foundation models, and AI. Students will work in teams, construct their ideas, and either program available hardware prototypes or build their hardware or software system.
Content
The course will involve learning both technical and project management skills which are essential in developing, designing, and prototyping practical systems where the underlying challenges fall in on or multiple areas with a focus on communication, signal processing, and AI, in particular multimodal foundation models.
The primary goal of this course is to give students hands-on experience with solving real-world challenges by working in teams to program different platforms and ultimately build their own projects. The overall structure of the course will consist of a introductory lectures at the beginning to introduce the project and research areas in wireless radar sensing, communication, computer vision, and foundational models. The students will have time to go through the background material needed for the course and get familiar with the tools and platforms. Students will then organize into groups of 3 or 4 and propose and develop their project with the aid of the course staff.
This class has two types of lectures.
(1) In person lectures at the beginning of the semester. After which the lecture time will be used as office hours to help students with their projects.
(2) Online lectures on background material.
The class will support 2 hardware platforms which students can work with for the wireless track.
Learning Prerequisites
Recommended courses
COM-102 Avanced Information, Computation, Communication II (BA2)
CS-202 Computer Systems (BA4)
COM-202 Signal Processing (BA4)
CS-Introduction to Machine Learning (BA4)
COM-302 Principles of Digital Communications (BA6) (To be taken concurrently)
Teaching methods
- lectures
- Tutorials on the hardware prototypes
- Continuous supervision and tutoring
- Extensive team work and team feedback
Expected student activities
- Take an entrepreneurial approach to create and develop a practical system under the given real-world constraints.
- Work with team members to complete a large practical project
- Independently research solutions, learn new concepts and apply them in practice.
- Debug software/hardware systems.
- Discuss project progress in class
- Provide constructive criticism and feedback to other groups
- Present project outcome in a public forum
Assessment methods
Individual activites: including homeworks, notebookes, and invidual progress.
Team project activities: including project proposals, presentations, and final report.
Supervision
| Office hours | Yes |
| Assistants | Yes |
| Forum | Yes |
Dans les plans d'études
- Semestre: Printemps
- Forme de l'examen: Pendant le semestre (session d'été)
- Matière examinée: Intelligent systems: communications & AI
- Cours: 2 Heure(s) hebdo x 14 semaines
- Projet: 10 Heure(s) hebdo x 14 semaines
- Type: optionnel
- Semestre: Printemps
- Forme de l'examen: Pendant le semestre (session d'été)
- Matière examinée: Intelligent systems: communications & AI
- Cours: 2 Heure(s) hebdo x 14 semaines
- Projet: 10 Heure(s) hebdo x 14 semaines
- Type: optionnel