Machine learning and data mining
- UE code IDASM102
-
Schedule
30 15Quarter 1
- ECTS Credits 5
-
Language
Anglais
- Teacher Frenay Benoît
At the end of the course, the student should be able to demonstrate an understanding of the different topics covered (see content), i.e. be able to express in his or her own words the theory and methods seen in the course and explain in what context they are useful. The student must also be able to apply the techniques seen in the course to simple data analysis problems and to document a current issue in machine learning and data mining.
The course introduces machine learning and data mining and will enable the student to tackle a wide range of data science problems. The following topics will be covered:
The course is divided into two learning activities. The first is the lectures and is assessed by an oral exam on the theory of the course. The second is a continuous assessment of the students' ability to implement the techniques seen in the course to solve simple data analysis problems. The examination and continuous assessment count for 70% and 30% of the course grade respectively.
References are given during the course.
Training | Study programme | Block | Credits | Mandatory |
---|---|---|---|---|
Master in Computer Science | Standard | 0 | 5 | |
Master in Computer Science, Professional focus in Data Science | Standard | 0 | 5 | |
Master in Mathematics, Professional focus in Data Science | Standard | 0 | 6 | |
Master in Business Engineering, Professional focus in Data Science | Standard | 0 | 6 | |
Master in Computer Science, Professional focus | Standard | 0 | 5 | |
Certificat d'université d'Executive Master en data science | Standard | 0 | 6 | |
Master in Physics, Professional focus in Physics and Data | Standard | 0 | 6 | |
Master in Computer Science, Professional focus in Data Science | Standard | 1 | 5 | |
Master in Business Engineering, Professional focus in Data Science | Standard | 1 | 6 | |
Master in Computer Science, Professional focus | Standard | 1 | 5 | |
Certificat d'université d'Executive Master en data science | Standard | 1 | 6 | |
Master in Physics, Professional focus in Physics and Data | Standard | 1 | 6 | |
Master in Computer Science | Standard | 1 | 5 | |
Master in Mathematics, Professional focus in Data Science | Standard | 2 | 6 |