25.00 credits
Q1 and Q2
This learning unit is not open to incoming exchange students!
Language
English
> French-friendly
> French-friendly
Main themes
The Master thesis is
The transversal competencies (referring to LO's) developed during the Master thesis are mainly: writing, communication, planning and argumentation, openness to the societal aspects of the project.
Information about master theses can be found on the dedicated Moodle web site https://moodleucl.uclouvain.be/course/view.php?id=11582
- the opportunity to acquire transversal competencies not yet or only partially developed previously;
- a project aiming at solving a complex engineering problem by applying competencies previously acquired.
The transversal competencies (referring to LO's) developed during the Master thesis are mainly: writing, communication, planning and argumentation, openness to the societal aspects of the project.
Information about master theses can be found on the dedicated Moodle web site https://moodleucl.uclouvain.be/course/view.php?id=11582
Learning outcomes
At the end of this learning unit, the student is able to : | |
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Content
The Master thesis may have a major “research” or “technological development” component. These components are however not exclusive; some theses may involve both dimensions, “research” and “technological development”.
The Master thesis may also be done in collaboration with industry.
The Master thesis may also be done in collaboration with industry.
Teaching methods
The student is responsible for the organisation of regular meetings with his/her director(s).
The student first prepare and hand in a thesis plan (roadmap) to his/her director(s) (and to program commission if requested) (deadline : 1 or 2 months after the beginning of the project).
The plan contains the following items (not necessarily all of them):
The student first prepare and hand in a thesis plan (roadmap) to his/her director(s) (and to program commission if requested) (deadline : 1 or 2 months after the beginning of the project).
The plan contains the following items (not necessarily all of them):
- clear statement of the objective(s),
- list of targeted LO’s (especially specific ones),
- context (application domain, societal impacts, ...),
- proposed methods (theory, experimental tools, developments,simulation, ...),
- list of available technical (equipments, codes, ...) and human
- first bibliographical research, including technical manuals,
- first schedule of tasks with deliverables.
Evaluation methods
Three grids (referring to LO’s) define criteria to evaluate the year's work, the manuscript and the oral defense.
The program commission may eventually add additional criteria.
The criteria are evaluated by a letter (A: excellent, B: very good, C: good, D: satisfactory, E: sufficient, F: failed, NA: not applicable).
A final note is then attributed.
If not otherwise stated in a document signed by both the master thesis supervisor and the student, the use of generative artificial intelligence to help writing the master thesis or some of its parts, or to write (parts of) a code, is not forbidden, provided the student indicates in the methodological part of his or her master thesis how and where these tools were used. Additionally, when part of the master thesis document is copied from a proposition made by an artificial intelligence, this specific AI tool needs to be referenced as the source of the text, as should be done for an excerpt of a published text.
The program commission may eventually add additional criteria.
The criteria are evaluated by a letter (A: excellent, B: very good, C: good, D: satisfactory, E: sufficient, F: failed, NA: not applicable).
A final note is then attributed.
If not otherwise stated in a document signed by both the master thesis supervisor and the student, the use of generative artificial intelligence to help writing the master thesis or some of its parts, or to write (parts of) a code, is not forbidden, provided the student indicates in the methodological part of his or her master thesis how and where these tools were used. Additionally, when part of the master thesis document is copied from a proposition made by an artificial intelligence, this specific AI tool needs to be referenced as the source of the text, as should be done for an excerpt of a published text.
Online resources
Rules and guidelines, important dates, templates and other information about master theses can be found on the dedicated Moodle web site https://moodleucl.uclouvain.be/course/view.php?id=11582
Faculty or entity
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Data Science Engineering