Code
MGFE PRO 5205
Level
M2
Field
Projet et gestion de projets
Language
Anglais/English
ECTS Credits
2
Class hours
10
Total student load
40
Program Manager(s)
Department
- Technologies, Information et Management
Educational team
Introduction to the module
This Data Analytics Hackathon course is an intensive, project-based learning experience where students work in teams to solve real-world data challenges under time constraints. It blends data exploration, analytics modeling, visualization, and storytelling: participants are given datasets and business or research problems, then apply data cleaning, statistical analysis, machine learning, and communication skills to derive insights and present solutions. The format encourages collaboration, creative problem-solving, iterative experimentation, and rapid prototyping—mirroring how analytics teams work in industry.
Partner companies propose real-world data sets with an issue to explore and to propose data-driven recommandation and solutions. The projects are conducted in groups with coaching by experts from partner enterprises. The projects presentations are realized in presence of the partner enterprises and in their offices.
Learning objectives/Intended learning outcomes
- 1.2 - Use digital intelligence tools efficiently to support the societal, digital, energy and environmental transformations of organisations, ensuring their sustainable and responsible impact.
- 2.2 - Drive creativity by mobilising ideation techniques and promoting interdisciplinarity and collaborative work to provide innovative solutions to complex issues in multicultural and international contexts.
- 3.2 - Communicate effectively and appropriately for the purposes of training, knowledge transfer, skills development or innovation, in English and at least one other language, in a global and multicultural context.
- 4.1 - Understand and apply complex project management methods in order to propose innovative strategic approaches that integrate the societal, digital, energy and/or environmental challenges that organisations may face.
Content : structure and schedule
- Presentation of the hackathon : goals, modalities, grading criteria
- Project presentation : the data sets and the corresponding questions
- Students group presentations
Sustainable Development Goals
Goal 9 - Industry, innovation and infrastructure
The course teaches advanced techniques and tools for developing innovative data-based solutions in all sorts of industries
Learning delivery
Mixte
Pedagogical methods
Group project
Evaluation and grading system and catch up exams
Grading via the evaluation of the project development and presentation
Catch-up exam via a 3h mini project
Textbook Required and Suggested Readings
Bruce, P., Bruce, A., & Gedeck, P. (2020). Practical Statistics for Data Scientists : 50+ Essential Concepts Using R and Python. O’Reilly Media.