Course description

Title of the Teaching Unit

Data Science and IA

Code of the Teaching Unit

21MQ061

Academic year

2026 - 2027

Cycle

Number of credits

Number of hours

Quarter

Weighting

Site

Montgomery

Teaching language

French

Teacher in charge

DENDONCKER Valentin

Objectives and contribution to the program

This course is an introduction to quantitative techniques for exploring and interpreting data, as well as data preparation techniques, with a view to using them in a project involving machine learning or artificial intelligence algorithms.
By the end of the course, students will be able to choose and apply a quantitative technique that will enable them to answer a question based on existing data.

Prerequisites and corequisites

Content

The course will cover the following topics:
- Data preparation techniques
- Supervised and unsupervised machine learning techniques

Teaching methods

Lectures combining descriptions of theoretical foundations, illustrations, and implementation of the concepts covered.

Artificial intelligence can be used to provide a more personalised learning experience.

Assessment method

The written exam (with no reference materials allowed) consists of multiple-choice and multiple-response questions, as well as possible open-ended questions.

The use of AI is not permitted during the exam.

References

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