Duration
150h Proj.
Number of credits
| Master of Science (MSc) in Data Science | 5 crédits | |||
| Master of Science (MSc) in Data Science and Engineering | 5 crédits |
Lecturer
Language(s) of instruction
English language
Organisation and examination
All year long
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
In this course, the student will carry out a personal project in data science, which can be a stand-alone data analysis, a piece of data science software, or a part of a larger, possibly interdisciplinary, project. We generally consider that it amounts to one month of full-time work.
The project topic is proposed by the student. It must be clearly specified and approved by the coordinator who will assign an advisor. The work achieved by the student in this project cannot be credited to any other of his/her courses.
Learning outcomes of the learning unit
The project aims at developing the students' ability to carry out a realistic data science project from the conceptual to the operational phase. The students will improve their creativity, autonomy, communication and writing skills.
This course contributes to the learning outcomes I.1, I.2, II.1, II.2, III.1, III.2, III.3, III.4, IV.1, IV.3, IV.4, V.1, V.3, VI.1, VII.1, VII.2, VII.3, VII.4, VII.5 of the MSc in data science and engineering.
Prerequisite knowledge and skills
Planned learning activities and teaching methods
- Feedback on technical progress,
- Writing of a final report,
- Defence and demonstration of the project.
Mode of delivery (face to face, distance learning, hybrid learning)
The project is mainly carried out remotely. The student will keep his/her advisor informed of his/her progress on a regular basis.
Recommended or required readings
Exam(s) in session
Any session
- In-person
oral exam
Written work / report
Additional information:
The evaluation will be based on the project completion report, the delivered analysis or system and its demonstration, and the project defence. There are no formal constraints on the size of the report, but it will typically be 20-page long. It should describe the context of the work, the problem addressed, the methodology, the accomplished tasks, the obtained results, and a conclusion (contributions and perspectives). It is necessary to provide enough quantitative information on the experimental analysis, the implemented system and the accomplished tests. The defence by the student is oral and public. It consists of an oral presentation, a question/answer session, and a short deliberation. The final grade considers the amount and quality of the completed work, the quality of the written report and the oral presentation, and the relevance of the provided answers.
Work placement(s)
Organizational remarks
- The final report must be submitted early January or early June.
- The defences and demonstrations will be scheduled in January or June
Contacts
Coordinator: Prof. Gilles Louppe (g.louppe@uliege.be)