Teaching

Since September 2024, I have been providing a full teaching service (~200h/year) at ISTIC, Université de Rennes. You can find below the list of disciplines I'm teaching

Graduate Students - Artificial Intelligence based Computer Vision

Master 2 IA, Université de Rennes, ISTIC, 2026

Artificial Intelligence based Computer Vision A set of lectures and practical work on Artificial Intelligence applied to computer vision :

  • computer vision before AI
  • Convolutional Neural Networks for computer vision
  • Reference networks in computer vision

Graduate Students - Artificial Intelligence & Design

Master 1 IA, Université de Rennes, ISTIC, 2026

We set-up a collaborative project between the Master 1 “Artificial Intelligence” and a school of design from Rennes (DSAA - Diplôme Supérieur d’Arts Appliqués de Rennes). The students of the 2 schools are thus able to collaborate on projects at the interface between design and artificial intelligence using public data from the Rennes metropolitan area.

Undergraduate Students - Unplugged Artificial Intelligence

Licence 1 ISTN, Université de Rennes, ISTIC, 2025

Unplugged Artificial Intelligence. We collectively set-up this collection of practical work for 1st year student to discover Artificial Intelligence through Unplugged (without computer) activities. I personnaly conceived 2 modules with my colleague Myriam Bontonou :

  • Planning & graphs paths
  • Markov Fields

Undergraduate Students - Probabilities & Statistics

Licence 2 ISTN, Université de Rennes, ISTIC, 2025

Probabilities and Statistics for undergraduate students :

  • Probabilities :
    • random variables
    • mean and variance
    • discrete and continuous probability laws
    • law of large numbers and central limit theorem
  • Statistics :
    • sampling
    • estimation and confidence intervals
    • hypothesis tests

Undergraduate Students - Information Theory

Licence 1 ISTN, Université de Rennes, ISTIC, 2025

Information Theory for undergraduate students :

  • number representation
  • numbering system
  • coding, compression (Shannon-Fano, Huffman)
  • error correcting codes

Undergraduate Students - Data science

Licence 2 ISTN, Université de Rennes, ISTIC, 2025

Data Science for undergraduate students :

  • Probabilities :
    • random variables
    • mean and variance
    • discrete and continuous probability laws
    • law of large numbers and central limit theorem
  • Statistics :
    • sampling
    • estimation and confidence intervals
    • hypothesis tests