In our Bachelor’s program, each student must obtain a certain number of credits by taking optional courses; this number of credits is 40 for the Bachelor of Computer Science. Each student is free to take any combination of optional courses that satisfy the credit requirement. However, students may find it difficult to choose.
To help them, we have put together some “option tracks”. An “option track” is a combination of electives that (a) create a meaningful plan of study, (b) satisfy the credit requirement, and (c) reasonably balance the student’s workload between semesters. In addition, some tracks include all courses required/recommended for a given master’s program. For example, the “ML and Quantum” track is an excellent way to prepare for the master’s degree in quantum science and engineering.
We would like to stress that the elective tracks are recommendations only and that each student is free and encouraged to create their own track that matches their personal interests – and to share their track to inspire friends and colleagues.
- Computer language processing [CS-320] – 6 credits (3rd year)
- Interaction personne système [CS-213] – 5 credits (2nd year)
- Introduction aux sciences du vivant [BIO-109] – 6 credits (2nd year)
- Numerical methods for visual computing and ML [CS-328] – 4 credits (2nd year)
- Systèmes embarqués microprogrammés [EE-390] – 5 credits (3rd year)
- Technologies for democratic society [CS-234] – 5 credits (2nd year)
To choose between:
- Computer graphics [CS-341] – 6 credits (3rd year)
- Introduction to machine learning [CS-233] – 5 credits (2nd year)
To choose between:
- Making Intelligent Things [CS-328] – 8 credits (3rd year)
- Projet de recherche optionnel en Informatique I [CS-304] – 8 credits (3rd year)
- Analyse IV [MATH-207(d)]- 4 credits (2nd year)
- General physics: electromagnetism [PHYS-114] – 4 credits (2nd year)
- Intelligence artificielle [CS-330] – 4 credits (3rd year)
- Internet analytics [COM-308] – 6 credits (3rd year)
- Introduction to machine learning [CS-233] – 6 credits (2nd year)
- Modèles stochastiques pour les communications [COM-300] – 6 credits (3rd year)
- Principles of digital communications [COM-302] – 6 credits (3rd year)
- Signal processing [COM-202] – 8 credits (2nd year – new course in autumn 2023)
- Introduction to machine learning [CS-233] – 6 credits (2nd year)
- Introduction to quantum computation [CS-308] – 5 credits (3rd year)
- Introduction to quantum information processing [COM-309] – 5 credits (3rd year)
- Mécanique analytique [PHYS-202] – 5 credits (2nd year)
- Numerical methods for visual computing and ML [CS-328] – 4 credits (2nd year)
- Optional research project in Quantum [CS-3xx] – 8 credits (3rd year)
- Quantum physics I [PHYS-313] – 5 credits (3rd year)
- Signal processing [COM-202] – 8 credits (2nd year – new course in autumn 2023)
- Introduction aux sciences du vivant [BIO-109] – 6 credits (2nd year)
- Biologie générale [BIOENG-110] – 6 credits (2nd year)
- Cellular and molecular biology I [BIO-205] – 3 credits (3rd year), outside of study plan
- Cellular and molecular biology [BIO-207] – 3 credits (3rd year), outside of study plan
- Intelligence artificielle [CS-330] – 4 credits (3rd year)
- Interaction personne-système [CS-213] – 5 credits (2nd year)
- Introduction to machine learning [CS-233] – 6 credits (2nd year)
- Numerical methods for visual computing and ML [CS-328] – 4 credits (2nd year)
- Signal processing [COM-202] – 8 credits (2nd year – new course in autumn 2023)
- Algebra [MATH-310] – 4 credits (2nd year)
- Computer language processing [CS-320] – 6 credits (3rd year)
- Interaction personne-système [CS-213] – 5 credits (2nd year)
- Internet analytics [COM-308] – 6 credits (3rd year)
- Introduction aux sciences du vivant [BIO-109] – 6 credits (2nd year)
- Introduction to machine learning [CS-233] – 6 credits (2nd year)
- Numerical methods for visual computing and ML [CS-328] – 4 credits (2nd year)
- Signal processing [COM-202] – 8 credits (2nd year – new course in autumn 2023)