Duration
15h Th, 10h Pr, 25h Proj.
Number of credits
| Bachelor of Science (BSc) in Engineering | 3 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The course provides an introduction to probability, as a language and set of tools for
understanding statistics, science, risk, and randomness.
The following topics are addressed:
- Probability and counting;
- Conditional probability and Bayes' rule;
- Discrete random variables;
- Continuous random variables;
- Joint distributions;
- Conditional expectation;
- Transformations;
- Inequalities and limit theorems.
Learning outcomes of the learning unit
At the end of the course, the student will be able to apply probabilistic methods to problems of reasoning under uncertainty, by being able to model them and identify the main resolution steps. He/she will also be knowledgeable about the main analytical and computational techniques useful to compute numerical solutions.
This course contributes to the learning outcomes I.1, I.2, II.1, III.1, III.2, IV.1, V.2, VI.1, VII.2 of the BSc in engineering.
Prerequisite knowledge and skills
The course relies on basic knowledge of calculus, algebra, geometry, and elements of computer science and applied mathematics.
Planned learning activities and teaching methods
The course includes ex-cathedra lectures, exercise sessions, and homework.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Recommended or required readings
The course material will be made available as the semester progresses.
Main reference:
- Blitzstein, Joseph K., and Jessica Hwang. Introduction to Probability. Second edition. Boca Raton: Taylor & Francis, 2019.
Exam(s) in session
Any session
- In-person
written exam
Written work / report
Work placement(s)
Organisational remarks and main changes to the course
Contacts
Lecturer: Pierre Sacré (p.sacre@uliege.be).
Webpage: https://people.montefiore.uliege.be/sacre/MATH0062/.