Artificial Intelligence has gained importance in the last decade with a lot depending on the development and integration of AI in our daily lives. The progress that AI has already made is astounding with the self-driving cars, medical diagnosis and even betting humans at strategy games like Go and Chess. The future for AI is extremely promising and it isn’t far from when we have our own robotic companions. This has pushed a lot of developers to start writing codes and start developing for AI and ML programs. However, learning to write algorithms for AI and ML isn’t easy and requires extensive programming and mathematical knowledge. Mathematics plays an important role as it builds the foundation for programming for these two streams. This course will help students master the mathematical foundation required for writing programs and algorithms for AI and ML. The course covers three main mathematical theories: Linear Algebra, Multivariate Calculus and Probability Theory.

Temps présentiel : 30 heures

Charge de travail étudiant : 70 heures

Méthode(s) d'évaluation : Examen final, Examen partiel