2023-2024 / MATH1222-3

Introduction to stochastic processes


20h Th, 10h Pr, 10h Mon. WS

Number of credits

 Bachelor of Science (BSc) in Computer Science5 crédits 
 Bachelor in mathematics4 crédits 


Céline Esser, Pierre Geurts


Pierre Geurts

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The course covers the following topics:

- Markov Chains (Definition, transition matrix and graph, state classifications, asymptotic behavior, mean time to first passage or return)

- Poisson Processes

- Markov Processes

- Queuing Theory

Learning outcomes of the learning unit

After the course, students will master the main properties of most classical stochastic processes.

Prerequisite knowledge and skills

good understanding of concepts in probability theory, matrix calculus, integral calculus, and graph theory.

Planned learning activities and teaching methods

In addition to the traditional classroom course, the course includes 10 hours traditional exercise sessions (10h Pr,  ex cathedra).

Students also have 10 hours of personal research work (10h TD). This work will be carried out in groups, and the guidelines will be provided during the theoretical class.

Mode of delivery (face to face, distance learning, hybrid learning)

Recommended or required readings

Course notes are available through eCampus. 

- Norris, James R. (1998). Markov chains. Cambridge University Press.
- Ross, Sheldon (2006). Introduction to probability models. Academic Press.

Any session :

- In-person

written exam ( open-ended questions )

- Remote

written exam ( open-ended questions )

- If evaluation in "hybrid"

preferred in-person

Additional information:

The final grade will be a weighted average of two grades :
- that obtained after a written exam held in June (concerning both theory and exercises);
- the grade obtained after evaluation of a project.


Work placement(s)

Organisational remarks and main changes to the course


Theory: C. Esser (Celine.Esser@uliege.be)

Exercises: A. Molla (A.Molla@uliege.be)

Project: P. Geurts (P.Geurts@uliege.be)

Association of one or more MOOCs