Université Grenoble Alpes
Master of Artificial Intelligence
Jointly delivered by UFR IM²AG and Ensimag (Grenoble INP). M1 is in progress.
Coursework arrives here as it is produced, semester by semester. Every M1 course is compulsory, so the order below is the order it is taught.
Semester 7
S7 · Python · C++
Programming
Python tooling and data, C++ and CMake, pybind11 interoperability, and a travelling-salesman solver.
S7 · APP
Algorithmic Problem Solving
Four projects — a maze, Candy Crush, school scheduling, hole drilling — solved by divide and conquer, dynamic programming, flows and approximation.
S7 · ML · Symbolic AI
Introduction to AI
Machine learning from evaluation metrics to recurrent networks, and symbolic AI in Datalog and constraint programming.
S7 · R
Applied Probability and Statistics
Four R labs, from vectorised code and first random draws to forecasting temperatures over France by kriging.
Operations research
Models that a solver decides
Linear and integer programs in OPL, then constraint models in pychoco: thirty-seven Caseine exercises, from a vegetable farm to car sequencing.
S7 · Python
Data Acquisition, Processing and Mining for AI
Weekly labs on pandas and DuckDB, and a paired project that pulls a live API, cleans what comes back, and mines it for something interpretable.