🎓 University Courses

🎓 University Courses#

Admission at Polytechnique#

https://www.polymtl.ca/futur/es/admission

Requirements for Polytechnique#

  • Details of the program on the Polymtl website.

  • The rules say that “At most 6 credits can be undergraduate courses and at least 8 credits must be courses in the field of biomedical engineering or other and approved by the CPÉS”, but this is a relaxed rules. Courses in computer science, deep learning, etc. are accepted.

  • For exemption of additional fees as foreign student, you need at least 6 credits completed, of grad courses at Polytechnique Montréal.

Writing your thesis

See this link.

Jury

Please refer to the Règlements généraux des études supérieures (53.4 COMPOSITION ET NOMINATION DU JURY).

  • Details of the program on the Polymtl website.

  • Candidates who already took courses in a previous graduate program (eg: Master) can obtain an exemption for some of the courses listed in the “Plan de cours” at Polytechnique. For more details, see article 73.1.1. To request the exemption, ask the form to Amal Bennani (biomedical-es@polymtl.ca). The procedure is to: (i) Fill up the “Plan de cours” with ONLY the courses to take, (ii) Fill up the document “EXEMPTION DE CREDITS DE COURS”, and list the courses that were taken at a previous graduate program, (iii) Send both documents to Amal.

Important

There exist an agreement between universities across Quebec, called CREPUQ, that allow students to transfer academic credits between institutions. So for example, you could attend a course at UdeM or McGill and receive the credits at Polytechnique Montreal as part of your gradutate program.

Writing your thesis

See this link.

Jury

Please refer to the Règlements généraux des études supérieures (76.4 COMPOSITION ET NOMINATION DU JURY).

Medical imaging#

Also see this list of Bio-imaging courses offered by Quebec Universities.

Polytechnique Montréal#

Code

Title / Notes

Credits

Lang.

Prof.

GBM8378

Principes d’imagerie biomédicale

3

🇫🇷

Julien Cohen-Adad

GBM6103A

Traitement d’images et signaux biomédicaux

3

🇫🇷

Goussard

GBM8770

Traitement numérique d’images médicales

3

🇫🇷

Benjamin De Leener

GBM6330

Technologies biomédicales émergentes

3

🇬🇧

Nikola Stikov

GBM6953EE

C.SPEC. Brainhack School
Must have!

3

🇬🇧

Eva Alonso Ortiz

Université de Montréal#

Code

Title / Notes

Credits

Lang.

Prof.

PSY6983

Projet en sciences des données neuronales
Excellent! Coding for open-science with neuro application (Andjela)

3

🇫🇷

?

PHY2300

Physique médicale

3

🇫🇷

?

PHY6985

Imagerie en physique médicale 1

3

🇫🇷

?

PHY6990

Imagerie en physique médicale 2

3

🇫🇷

?

PSY3018B

Méthodes en neurosciences cognitives 2

3

🇫🇷

Pierre L Bellec

McGill#

Code

Title / Notes

Credits

Lang.

Prof.

MDPH607

Introduction to Medical Imaging

3

🇬🇧

Ives Levesque

BMDE650

Advanced Medical Imaging

3

🇬🇧

Louis Collins, Amir Shmuel

BMDE660

Advanced MR Imaging and Spectroscopy of the Brain
Excellent but need to put in extra hours (Nadia, Andjela)

3

🇬🇧

Christine Tardif, David Rudko

NEUR606

Methods in Neuroimaging

3

🇬🇧

Nathan Spreng

NEUR602

Current Topics in Neuroscience

3

🇬🇧

?

QLSC612

Fundamentals for Neuro Data Science
1-week 8am-5pm summer intensive. Manageable and pairs well with Brainhack summer course (Andjela)

3

🇬🇧

?

Machine Learning / Statistics#

Polytechnique Montréal#

Code

Title / Notes

Credits

Lang.

Prof.

INF8245E

Machine Learning

3

🇬🇧

Sarath Chandar

INF8250E

Reinforcement Learning

3

🇬🇧

Sarath Chandar

MTH6312

Méthodes statistiques d’apprentissage
Trés théorique

3

🇫🇷

Luc Adjengue

MTH6305A

Reconnaissance de formes: approches statistiques

3

🇫🇷

?

INF6953H

C.SPÉC.: Deep Learning

3

🇬🇧

Chris Pal

MTH3302

Probabilité et statistiques pour intelligence artificielle

3

🇫🇷

Jonathan Jalbert

INF8215

Intelligence artif.: méthodes et algorithmes

3

🇫🇷

Daniel Aloise

INF8225

I.A.: tech. probabilistes et d’apprentissage
Cours intense (Andréanne)

3

🇫🇷

Chris Pal

Université de Montréal#

Code

Title / Notes

Credits

Lang.

Prof

BIO2043B

Statistique pratique pour sciences de la vie
First 4 classes not really relevant, Last 4 classes interesting, on Pearson, Kendall correlation, Multiple Regressions, ANOVA (Maxime)

3

🇫🇷

?

IFT6268

Self-Supervised Representation Learning

4

🇬🇧

Aaron Courville

IFT6269

Probabilistic Graphical Models
Given in Fall. Math heavy, assignment with proofs + coding exercises. Really interesting course! (Naga)

4

🇬🇧

Simon Lacoste-Julien

IFT6135H

Representation Learning
Intense course but very rewarding (Naga)

4

🇬🇧

Aaron Courville

IFT6167H

Neural Scaling Laws and Foundation Models
Easy course, project-based (Naga)

4

🇬🇧

Irina Rish

IFT6758A

Data Science

4

🇬🇧

Gauthier Gidel, Glen Berseth

IFT6760

Seminars in deep learning

?

?

Mcgill#

Code

Title / Notes

Credits

Lang.

Prof.

BMDE520A

Machine Learning for Biomedical Data
Assignment heavy, no CV application (Rohan)

3

🇬🇧

Danilo Bzdok

COMP551AH

Applied Machine Learning outline
Great overview of classical ML but not much DL. No CV. (Nadia)

4

🇬🇧

Yue Li (Fall), Reihaneh Rabbany (Winter)

Computer Vision#

Polytechnique Montréal#

Code

Title / Notes

Credits

Lang.

Prof.

GBM6700

Reconstruction 3D à partir d’images médicales Curriculum

3

🇫🇷

Cheriet

ELE8812

Traitement et analyse d’images

3

🇫🇷

Eva Alonso Ortiz

Université de Montréal#

Code

Title / Notes

Lang.

Prof.

IFT6145

3D Vision (Vision tridimensionnelle)

French

Sebastien Roy

McGill#

Electrical and Computer Engineering Course List: http://www.mcgill.ca/ece/programs/coursesoffered/500

Code

Title / Notes

Lang.

Prof.

ECSE 683

Topics in Vision and Robotics

(Fall 2013)

English

Frank Ferrie

ECSE 626

Statistical Methods in Computer Vision

Slides 2019

(Requires a fair bit of involvement but very interesting and cutting edge. Who took it: Charley Gros, Rohan Banerjee, Kiri Stern)

English

Tal Arbel

COMP 424

Introduction to Artificial Intelligence

English

Doina Precup

COMP 558

Fundamentals of Computer Vision

(Fall 2013)

English

Kaleem Siddiqi

COMP 766

Shape Analysis in Computer Vision

(Winter 2014)

English

Kaleem Siddiqi

Programming & Software#

  • INF1010 - Programmation orienté objet (C++)

  • https://www.polymtl.ca/programmes/cours/langages-de-script / INF8007 (1 credit)

Biomedical#

Polytechnique Montréal#

Code

Title / Notes

Lang.

Prof.

GBM8871

Biomicrosystèmes

(time-consuming)

Français

Thomas Gervais

GBM8802

Biophotonique

(time-consuming)

Français

Boudoux

GBM8605

Médecine régénératrice & nanomédecine

(not hard, a bit time-consuming)

Français

Buchmann

PHS3210

Spectroscopie

(difficult)

Français

Sébastien Francoeur

Instrumentation / RF Coils#

Polytechnique Montréal#

Code

Title / Notes

Lang.

Prof.

ELE1600A

Circuit électrique

Français

Chahé Nerguizian

GBM2330

Instrumentation et mesures biomédicales

Français

Nikola Stikov

ELE6503

Dispositifs et circuits actifs micro-ondes

Français

Jean-Jacques Laurin

ELE6506

Antennes et propagation

Français

Jean-Jacques Laurin

ELE4501A

Circuits et systèmes communications radiofréquences

(laboratoire simulation ADS Agilent)

Français

Ke Wu

ELE6502

Instrumentation automatisée en micro-ondes

Français

Cevdet Akyel

ELE8500

Circuits Passifs Micro-ondes

(laboratoires d’initiation aux analyseurs de réseau et de spectre)

Français

Ke Wu

McGill#

Code

Title / Notes

Lang.

Prof.

BMDE501

Selected Topics in Biomedical Engineering

(3 credits)

English

BMDE503

Biomedical Instrumentation

(3 credits)

English

Language Courses#

Polytechnique Montréal#

Code

Title / Notes

Lang.

Prof.

SSH3351

Anglais pour ingenieurs 1

Français

SSH3352

Anglais pour ingenieurs 2

Français

McGill#

Code

Title / Notes

Lang.

Prof.

Graphos

Academic writing

English

Ethics#