| Course label : | Data challenge |
|---|---|
| Teaching departement : | EEA / Electrotechnics - Electronics - Control Systems |
| Teaching manager : | Mister PIERRE-ANTOINE THOUVENIN / Mister PIERRE CHAINAIS |
| Education language : | |
| Potential ects : | 0 |
| Results grid : | |
| Code and label (hp) : | MR_DS_S4_DCH - Data challenge |
Education team
Teachers : Mister PIERRE-ANTOINE THOUVENIN / Mister PIERRE CHAINAIS
External contributors (business, research, secondary education): various temporary teachers
Summary
A short-term data challenge will be proposed to students (either by pairs or groups) over a short period of time (up to 3 to 4 weeks) so that they can get familiar with the methodology of the participation to a Kaggle competition thanks to team collaboration. This project will be based on some datasets and will be supervised by a team of coaches/supervisors.
Educational goals
After successfully taking this course, a student should be able to: ● participate to a data challenge, ● handle brute datasets, ● give a presentation of his results and methods ● work in a team and collaborate with others.
Sustainable development goals
Knowledge control procedures
Continuous Assessment
Comments: Report + final presentation + score: grading scale: (min) 0 – 20 (max)
Passing grade = 10/20
Online resources
Articles from the literature provided by the supervisor.
Pedagogy
Language of instruction is specified in the course offering information in the course and programme directory. English is the default language.
Sequencing / learning methods
| Number of hours - Lectures : | 0 |
|---|---|
| Number of hours - Tutorial : | 24 |
| Number of hours - Practical work : | 0 |
| Number of hours - Seminar : | 0 |
| Number of hours - Half-group seminar : | 0 |
| Number of student hours in TEA (Autonomous learning) : | 0 |
| Number of student hours in TNE (Non-supervised activities) : | 0 |
| Number of hours in CB (Fixed exams) : | 0 |
| Number of student hours in PER (Personal work) : | 0 |
| Number of hours - Projects : | 0 |
Prerequisites
M1 Data science