Master thesis in data analytics

ldate2990  2022-2023  Louvain-la-Neuve

Master thesis in data analytics
25.00 credits
Q1 and Q2

  This learning unit is not open to incoming exchange students!

Language
Main themes
The Master thesis is
-          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 Master thesis may have a major 'research' or 'technological development' component. These components are however not exclusive; some theses may involve both dimensions.
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 :

1 LO1 to demonstrate he/she masters a body of knowledge and basic skills in science and/or engineering sciences, bound about his/her thesis;
LO2 to lead to completion a major, in amplitude and spent time, engineering approach applied to the development of a product, service or facility referred to the thesis (applies to theses with a major technological development component) ;
LO3 to lead to completion a major, in amplitude and spent time, research work aiming at the understanding and the contribution to the resolution of an original scientific question of theoretical or physical type (applies to theses with a major research component. They are however not exclusive; some theses may involve both dimensions, research and development) ;
LO4 to organise and plan the master thesis work on the basis of allocated resources and time constraints, of security (if applicable) and of available competencies ;
LO5 to efficiently communicate both orally and in writing (in French and/or in English) to realise the master thesis ;
LO6 to take into account the societal impact of his/her master thesis (possible economical recovery and/or ethical impact and/or environmental and/or social impact).
Specific learning outcomes are defined on the Moodle web site.
 
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.
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):
  • 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
(supervisors, and resource persons for technical aspects) resources,
  • 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.
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
EPL


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Data Science Engineering