  Big data, data science, deep learning, artificial intelligence are the key
words of intense hype related with a job market in full evolution, that impose
to adapt the contents of our university professional trainings. Which
artificial intelligence is mostly concerned by the job offers? Which
methodologies and technologies should be favored in the training programs?
Which objectives, tools and educational resources do we needed to put in place
to meet these pressing needs? We answer these questions in describing the
contents and operational resources in the Data Science orientation of the
specialty Applied Mathematics at INSA Toulouse. We focus on basic mathematics
training (Optimization, Probability, Statistics), associated with the practical
implementation of the most performing statistical learning algorithms, with the
most appropriate technologies and on real examples. Considering the huge
volatility of the technologies, it is imperative to train students in
seft-training, this will be their technological watch tool when they will be in
professional activity. This explains the structuring of the educational site
github.com/wikistat into a set of tutorials. Finally, to motivate the thorough
practice of these tutorials, a serious game is organized each year in the form
of a prediction contest between students of Master degrees in Applied
Mathematics for IA.
