I teach the following courses:
Sûreté de fonctionnement et Retour d'expériences ( Reliability and Feedback Data Collection) ,
4th Year of Engineering in Management opérationnel Maintenance et Maîtrise des risques (M3)
- Course Slides: CM1, CM2, CM3, CM4, CM4b, CM5etCM6
- TDs (Tutorials): TD1, TD2, TD3, TD4
- Solutions TD: TD1, TD2, TD3, TD4
- Gamma Function Table
Introduction to Deep Learning and Artificial Intelligence (5th year, Ingénierie de l’Information et des Systèmes (FISE & FISA) :
- Theory: Basics, ANN, CNNs, RNNs and LSTM.
- Practicals: In Jupyter notebook, ANN: classification MNIST data, MNIST fashion data; CNN based: CIFAR data classification, LSTM based: prediction of time series
- Slides available at request.
- Student Feedback ( in French) 2019-20, 2020-2021,
Introduction to Reinforcement Learning and Deep Reinforcement Learning for Control
- Theory: Basics, Markov Decision Processes, Dynammic Programming, Model free control (SARSA and TD control), Function Approximation (Deep Neural netowrks),
- Deep reinforcement Leanring ( DQN and DDPG).
- Environments solved in Tutorials (OpenAI gym based Environments)
Cartpole, Inverted Pendulum and Bipedal Walker
Decision support and Artifical Intelligence for Predictive Maintenance (5th Year, M3)
- Decision support ( multi-criteria decision making): AHP, TOPISIS
- Deep Neural networks for decision: ANNS RNNs
- Deep Learning based Prognostics for Predictive maintenance: CM1
Digital Signal processing (Traitement du signal numérique), 4th Year, Tutorials and Practicals (TD et TPs) , M3)
Control of Mobile Robots (5A IA2R Parcours SIA)
Lab 1: The QCAR (Autonomous Car),
Lab 2: The QBOT (differential drive robot by Quanser)
Lab3: The 3Pi+ Robot
Lab4: The Zumo robot