Romain Couillet

Courses

University ParisSaclay
- Master MVA (Cachan). Random Matrix Theory and Applications to Machine Learning (since 2014)
  - 36 hours, Master level
  - Course notes (in French)
  - Slides (in English)

Grenoble-INP
- ENSIMAG. Introductory Courses to Supervised Learning (since 2020)
  - 18 hours, undergraduate level
  - Course notes (in French)
- ENSIMAG. Algorithms and Data Structures (since 2020)
  - Exercises (TDs, 12 * 1.5h), undergraduate level
  - TD1 Jupyter Notebook [ipynb|html]
  - TD2 Jupyter Notebook [ipynb|html]
  - TD3 Jupyter Notebook [ipynb|html]
  - TD4 Jupyter Notebook [ipynb|html]
  - TD5 Jupyter Notebook [ipynb|html]
  - TD6 Jupyter Notebook [ipynb|html]
  - TD7 Jupyter Notebook [ipynb|html]
  - TD8 Jupyter Notebook [ipynb|html]
  - TD9 Jupyter Notebook [ipynb|html]
  - TD10 Jupyter Notebook [ipynb|html]
  - TD11 Jupyter Notebook [ipynb|html]
- PHELMA (master SIGMA). Introductory Course on Optimization (since 2018)
  - 18 hours, master level
  - Course notes, Slides
- PHELMA (master SIGMA). Scientific Writing for Engineering and Master Students (since 2019)
  - 9 hours, master level
  - Slides

University Grenoble-Alpes
- UFR IM2AG (L1 MINint). Functional Programming with OCaml (since 2020)
  - 69 hours, undergraduate level
  - Course 0 - General Information
  - Course 1 - Introduction, simple expressions and simple types (notebook|html|ml)
  - Course 2 - Identifiers and functions (notebook|html|ml)
  - Course 3 - Advanced types (notebook|html|ml)
  - Course 4 - Recursion (notebook|html|ml)
  - Course 5 - Lists (notebook|html|ml)
  - Course 6 - Polymorphism and higher order (notebook|html|ml)
  - Course 7 - Tree structures (notebook|html|ml)
- MoSIG Master. Fairness in Machine Learning (since 2020)
  - 3 hours, Master level
  - Slides
- ED EEATS. Scientific Communication for PhD Students (since 2012)
  - 18 hours, PhD level
  - Slides