Study Programmes 2017-2018
Elements of probability calculus
Duration :
15h Th, 15h Pr, 5h Proj.
Number of credits :
Bachelor in computer science3
Master in data science (120 ECTS)3
Master of science in computer science and engineering (120 ECTS)3
Lecturer :
Pascal Gribomont
Language(s) of instruction :
French language
Organisation and examination :
Teaching in the first semester, review in January
Units courses prerequisite and corequisite :
Prerequisite or corequisite units are presented within each program
Learning unit contents :
Basic notions of probability theory: combinatorics, discrete random variables, continuous random variables (basics), probability laws, limit theorems.
Learning outcomes of the learning unit :
The student will be able to recognize elementary probabilistic problems and the corresponding discrete random variables. He will solve these problems and write the necessary computer programs.
Prerequisite knowledge and skills :
Elementary computer programming.
Elementary algebra, elementary calculus.
Planned learning activities and teaching methods :
Theoretical lectures and supervised problem solving sessions.
Mode of delivery (face-to-face ; distance-learning) :
Face-to-face. Thursday at 8:15, R21.
Recommended or required readings :
A First Course in Probability, by Sheldon Ross, 8th or 9th edition.

See also
Assessment methods and criteria :
Programming project. Written examination in January.
Work placement(s) :
Organizational remarks :
Contacts :
Pascal Gribomont Isabelle Mainz