2024-2025 / Master

MSc. in Data Science and Engineering, professional focus

120 crédits

Cycle view

  • Bloc
  • Organization
  • Theory
  • Practical
  • Others
  • Credits
If one or several of the mandatory courses have already been credited when entering the Master of Data science program, they can be replaced by a corresponding amount of credits chosen among the elective courses.

Focus courses

B1
30Cr
CodeDetailsBlocOrganizationTheoryPracticalOthersCredits
ELEN0062-1
Introduction to machine learning (english language) - [40h Projet]
Corequisite
INFO8006-1
Introduction to artificial intelligence
B1Q1305[+]5
INFO8010-1
Deep learning (english language) - [60h Projet] B1Q230-[+]5
INFO9014-1
Knowledge representation and reasoning (english language) - [45h Projet] B1Q22420[+]5
INFO9016-1
Advanced Databases (english language) - [20h Projet]
Corequisite
INFO0009-2
Bases de données (organisation générale)
B1Q22420[+]5
DATS0001-1
Foundations of data science (english language) - [60h Projet] B1Q130-[+]5
MATH2021-1
High-dimensional statistics (english language) - [30h Projet] B1Q13015[+]5

Compulsory courses from the core curriculum

B1
5Cr
B2
35Cr
CodeDetailsBlocOrganizationTheoryPracticalOthersCredits
PROJ0021-1
Data science project (english language) - [120h Projet]
Corequisite
INFO0902-1
Structures des données et algorithmes
B1Q25-[+]5
DROI1357-1
European law, (big) data and artificial intelligence applications seminar (english language) B2Q124--5
GEST3162-1
Principles of management (english language) - [25h Projet] B2Q130-[+]5
ATFE9009-1
Master thesis (english language) - [750h Projet] B2TA--[+]25
[...] Students who have already acquired the skills and knowledge of GEST3162 (or equivalent) will replace it by a course of their choice of 5 ECTS5

Optional courses from the core curriculum

B1
25Cr
B2
25Cr

In agreement with the Jury, choose a total of 25 credits for Block 1 and 25 credits for Block 2 in the following list, among those that have not already been credited before.

B1
25Cr
B2
25Cr
CodeDetailsBlocOrganizationTheoryPracticalOthersCredits
Data Science foundation courses
The following courses (INFO0009-2, INFO8006-1, MATH0461-2 and INFO0902-1) are corequisite to some compulsory courses of the master program. They must be taken as a priority, unless they were already taken as part of the bachelor of science in engineering or bachelelor of computer science, or unless the corresponding knowledge and skills have been acquired previously.
INFO0009-2
Database (general organisation) - [25h Projet] B1Q22626[+]5
INFO8006-1
Introduction to artificial intelligence (english language) - [45h Projet] B1Q12520[+]5
MATH0461-2
Introduction to numerical optimization (english language) - [25h Projet] B1Q13020[+]5
INFO0902-1
Data structures and algorithms - [40h Projet] B1Q22620[+]5
ELEN0016-2
Computer vision (english language) - [50h Projet] -Q13010[+]5
ELEN0060-2
Information and coding theory (english language) - [30h Projet] -Q23015[+]5
INFO0016-1
Introduction to the theory of computation (english language) -Q12626-5
INFO0027-2
Programming techniques (english language) -Q2   5
Algorithmics - [40h Projet]   1414[+] 
Software patterns - [30h Projet]   1010[+] 
INFO0054-1
Functional programming - [20h Projet] -Q12424[+]5
INFO0939-1
High performance scientific computing (english language) - [20h Projet] -Q13015[+]5
INFO0948-2
Introduction to intelligent robotics (english language) - [80h Projet] -Q2304[+]5
INFO2049-1
Web and Text Analytics (english language) -Q130--5
INFO8003-1
Reinforcement learning (english language) - [45h Projet] -Q22510[+]5
INFO8004-1
Advanced Machine learning (english language) - [20h Projet] -Q225-[+]5
INFO9012-1
Parallel Programming (english language) -Q22525-5
INFO9015-1
Logic for Computer Science (english language) -Q12420-5
MATH0462-1
Discrete optimization (english language) - [25h Projet] -Q23020[+]5
MATH2022-1
Monte Carlo methods in statistics (english language) - [40h Projet] (Even years, organized in 2024-2025) -Q22412[+]5
MQGE0002-3
Computational Optimization (english language) -Q230--5
BIOL0021-1
Biology of the systems - [10h Monitored workshops]
Corequisite
OCEA0089-1
Introduction to marine ecosystems modelling
-Q110-[+]2
OCEA0089-1
Introduction to marine ecosystems modelling (english language)
Corequisite
BIOL0021-1
Biologie des systèmes
-Q11515-3
GEOG0057-1
Spatial analysis -Q23030-5
GEOG0059-1
Infrastructures of spatial data -Q13030-5
GEST0832-4
Financial Markets -Q24015-5
FINA0063-1
Advanced Statistical Methods in Finance (english language) -Q130--5
GEST3032-1
e-Commerce Methods and Techniques (english language) -Q130--5
GBIO0002-1
Genetics and bioinformatics (english language) - [15h Projet] -Q13015[+]5
GBIO0030-1
Computational approaches to statistical generics (english language) - [35h Projet] -Q22515[+]5
SPAT0263-1
Machine Learning in Space Sciences (english language) -Q13015-5
SPAT0264-1
Machine Learning for Gravitational-wave Astronomy (english language) -Q21020-5
INFO9023-1
Machine Learning Systems Design (english language) - [17h Laboratory work, 18h Projet]
Corequisite
ELEN0062-1
Introduction to machine learning
-Q217-[+]5
MATH1222-3
Introduction to stochastic processes - [10h Monitored workshops] -Q22010[+]5
SYST0022-1
Linear Systems Design (english language) - [15h Projet] -Q22626[+]5

Optional company internship

ASTG9009-1
Internship (independent of Master thesis) - [40d Field work] B2TA--[+]10
[...] With the agreement of the President of the Jury, students may also choose up to 15 credits in the application area of their Master thesis in other programmes of the university -
[...] With the agreement of the President of the Jury, students may also choose 5 credits in any other programme of the university or from the UNIC course catalog-

Bridging courses Master MSc. in Data Science and Engineering (120 credits) 2024-2025

CodeDetailsBlocOrganizationTheoryPracticalOthersCredits
Students who are admitted to this master without having acquired equivalent courses must add them to the programme of their first year.

1. Basic courses of a bachelor degree of science in engineering, including courses equivalent to :
MATH0002-4
Mathematical analysis 1, Part 1 B0Q12222-5
MATH0013-1
Algebra B0Q12626-4
MATH0062-1
Elements of probability calculus - [25h Projet] B0Q21510[+]3
MATH0487-2
Elements of statistics - [25h Projet] B0Q11510[+]3
MATH1222-3
Introduction to stochastic processes - [10h Monitored workshops] B0Q22010[+]5
INFO2009-2
Introduction to computer science B0Q12414-4
MATH0006-3
Introduction to numerical analysis (english language) B0Q12020-4
MECA0003-2
Rational Mechanics B0Q12030-4
SYST0002-2
Introduction to signals and systems - [15h Projet] B0Q22626[+]5

2.  Additional courses in computer science :
INFO0902-1
Data structures and algorithms - [40h Projet] B0Q22620[+]5
INFO0009-2
Database (general organisation) - [25h Projet] B0Q22626[+]5
INFO8006-1
Introduction to artificial intelligence (english language) - [45h Projet] B0Q12520[+]5

3. A level B2 in English

Bridging courses Master in Data Science Engineering (120 credits)

CodeDetailsBlocOrganizationTheoryPracticalOthersCredits
Students who are admitted to this master without having acquired equivalent courses must add them to the programme of their first year.

1. Basic courses of a bachelor degree of science in engineering, including courses equivalent to :
MATH0002-4
Mathematical analysis 1, Part 1 B0Q12222-5
MATH0013-1
Algebra B0Q12626-4
MATH0062-1
Elements of probability calculus - [25h Projet] B0Q21510[+]3
MATH0487-2
Elements of statistics - [25h Projet] B0Q11510[+]3
INFO2009-2
Introduction to computer science B0Q12414-4
MATH0006-3
Introduction to numerical analysis (english language) B0Q12020-4
MECA0003-2
Rational Mechanics B0Q12030-4
SYST0002-2
Introduction to signals and systems - [15h Projet] B0Q22626[+]5

2.  Additional courses in computer science :
INFO0902-1
Data structures and algorithms - [40h Projet] B0Q22620[+]5
INFO0009-2
Database (general organisation) - [25h Projet] B0Q22626[+]5
INFO8006-1
Introduction to artificial intelligence (english language) - [45h Projet] B0Q12520[+]5

3. A level B2 in English