The professional masters in machine learning combines specialized coursework, with emphasis on the MILA artificial intelligence classes, and work experience in the artificial intelligence industry.
Applicants should consult the MILA recruitment procedure, indicating they are applying for the industrial masters. Once accepted, they can apply to the relevant department, and the MILA will take care of finding internship and guiding the students during their work.
Recommended classes
- IFT 6080 – Duckietown
- IFT 6085 – Advanced Structured Prediction
- IFT 6135 – Learning representations
- IFT 6266 – Learning algorithms
- IFT 6285 – Natural Language Processing
- IFT 6269 – Probabilistic graphical models and learning
- IFT 6390 – Fondamentals of Machine Learning
- INF 6953H (Poly) – Deep Learning
- INF 8225 (Poly) – Probabilistic techniques and learning
- INF 8702 (Poly) – Advanced Computer Graphics
- MTH6404 (Poly) – Integer Programming
- 6-602-07 (HEC)- Applied multidimensional analysis
- 80-629-17A (HEC) – Machine Learning for Large-Scale Data Analysis & Decision Making
- COMP 550 (McGill)- Natural Language Processing
- COMP 551 (McGill) – Applied Machine Learning
- COMP 652 (McGill) – Machine Learning
- COMP 767 (McGill) – Advanced Topics: Reinforcement learning
Université de Montréal: Masters in Computer Science (internship option)
The program starts with 6 graduate level classes. This is followed by a 6 months internship in industry or in an academic laboratory. Students are supervised by a professor and a staff member from the MILA research and development team, who provide daily guidance and linkage with industrial partners.
Internship procedure
Internship documents (French)