Vue cycle
- Bloc
- Organisation
- Théorie
- Pratique
- Autres
- Crédits
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.
| Code | Détails | Bloc | Organisation | Théorie | Pratique | Autres | Crédits |
|---|---|---|---|---|---|---|---|
| PROJ0021-1 | Data science project (anglais) - [120h Projet]
Corequis
| B1 | Q2 | 5 | - | [+] | 5 |
| DROI1357-1 | European law, (big) data and artificial intelligence applications seminar (anglais) | B2 | Q1 | 24 | - | - | 5 |
| GEST3162-1 | Principles of management (anglais) - [25h Projet] | B2 | Q1 | 30 | - | [+] | 5 |
| ATFE9009-1 | Master thesis (anglais) - [750h Projet] | B2 | TA | - | - | [+] | 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 ECTS | - | |||||
Optional courses from the core curriculum
- B1
- 25Cr
- B2
- 25Cr
| Code | Détails | Bloc | Organisation | Théorie | Pratique | Autres | Crédits |
|---|---|---|---|---|---|---|---|
| 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. |
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| INFO8006-1 | Introduction to artificial intelligence (anglais) - [45h Projet] | B1 | Q1 | 25 | 20 | [+] | 5 |
| MATH0461-2 | Introduction to numerical optimization (anglais) - [25h Projet] | B1 | Q1 | 30 | 20 | [+] | 5 |
| INFO0009-2 | Bases de données (organisation générale) - [25h Projet] | B1 | Q2 | 26 | 26 | [+] | 5 |
| INFO0902-1 | Structures des données et algorithmes - [40h Projet] | B1 | Q2 | 26 | 20 | [+] | 5 |
| DATS0002-1 | Data visualization (anglais) - [25h Projet] | - | Q2 | 25 | 20 | [+] | 5 |
| ELEN0016-2 | Computer vision (anglais) - [50h Projet] | - | Q1 | 30 | 10 | [+] | 5 |
| ELEN0060-2 | Information and coding theory (anglais) - [30h Projet] | - | Q2 | 30 | 15 | [+] | 5 |
| ELEN0449-1 | Computer Vision understanding (anglais) - [50h Projet] | - | Q2 | 24 | 10 | [+] | 5 |
| INFO0016-1 | Introduction to the theory of computation (anglais) | - | Q1 | 26 | 26 | - | 5 |
| INFO0027-2 | Programming techniques (anglais) | - | Q2 | 5 | |||
| Algorithmics - [40h Projet] | 14 | 14 | [+] | ||||
| Software patterns - [30h Projet] | 10 | 10 | [+] | ||||
| INFO0939-1 | High performance scientific computing (anglais) - [20h Projet] | - | Q1 | 30 | 15 | [+] | 5 |
| INFO0948-2 | Introduction to intelligent robotics (anglais) - [80h Projet] | - | Q2 | 30 | 4 | [+] | 5 |
| INFO2049-1 | Artificial Intelligence Methods for Natural Language Processing (anglais) | - | Q1 | 30 | - | - | 5 |
| INFO8003-1 | Reinforcement learning (anglais) - [45h Projet] | - | Q2 | 25 | 10 | [+] | 5 |
| INFO8004-1 | Advanced Machine learning (anglais) - [20h Projet] | - | Q2 | 25 | - | [+] | 5 |
| INFO9015-1 | Logic for Computer Science (anglais) | - | Q1 | 24 | 20 | - | 5 |
| INFO9023-1 | Machine Learning Systems Design (anglais) - [17h Laboratoire, 18h Projet]
Corequis
| - | Q2 | 17 | - | [+] | 5 |
| INFO9030-1 | Explainable Artificial Intelligence (anglais) - [50h Projet]
Corequis
| - | Q2 | 24 | - | [+] | 5 |
| MATH0462-1 | Discrete optimization (anglais) - [25h Projet] | - | Q2 | 30 | 20 | [+] | 5 |
| MATH1222-3 | Introduction aux processus stochastiques - [10h Travaux dirigés] | - | Q2 | 20 | 10 | [+] | 5 |
| MATH2022-1 | Monte Carlo methods in statistics (anglais) - [40h Projet] (années paires, organisé en 2026-2027) | - | Q2 | 24 | 12 | [+] | 5 |
| MQGE9007-1 | Advanced Modeling Techniques in Optimization (anglais)
Quentin Louveaux, N...
| - | Q1 | 30 | - | - | 5 |
| SYST0022-1 | Linear Systems Design (anglais) - [15h Projet] | - | Q2 | 26 | 26 | [+] | 5 |
| BIOL0021-1 | Biologie des systèmes - [10h Travaux dirigés]
Corequis
| - | Q1 | 10 | - | [+] | 2 |
| OCEA0089-1 | Introduction to marine ecosystems modelling (anglais)
Corequis
| - | Q1 | 15 | 15 | - | 3 |
| GEOG0057-1 | Analyse spatiale | - | Q2 | 30 | 30 | - | 5 |
| GEOG0059-1 | Infrastructures de données spatiales | - | Q1 | 30 | 30 | - | 5 |
| GEST0832-4 | Marchés financiers | - | Q2 | 40 | 15 | - | 5 |
| FINA0063-1 | Advanced Statistical Methods in Finance (anglais) | - | Q1 | 30 | - | - | 5 |
| GEST3032-1 | eCommerce Methods and Techniques (anglais) | - | Q1 | 30 | - | - | 5 |
| SPAT0263-1 | Machine Learning in Space Sciences (anglais) | - | Q1 | 30 | 15 | - | 5 |
| SPAT0264-1 | Machine Learning for Gravitational-wave Astronomy (anglais) | - | Q2 | 10 | 20 | - | 5 |
Optional company internship |
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| ASTG9009-1 | Internship (independent of Master thesis) - [40j Travail sur le terrain] | B2 | TA | - | - | [+] | 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 | - | |||||
| Code | Détails | Bloc | Organisation | Théorie | Pratique | Autres | Crédits |
|---|---|---|---|---|---|---|---|
| DATS0001-1 | Foundations of data science (anglais) - [60h Projet] | B1 | Q1 | 30 | - | [+] | 5 |
| ELEN0062-1 | Introduction to machine learning (anglais) - [40h Projet]
Corequis
| B1 | Q1 | 30 | 5 | [+] | 5 |
| INFO9016-1 | Advanced Databases (anglais) - [20h Projet]
Corequis
| B1 | Q1 | 24 | 20 | [+] | 5 |
| MATH2021-1 | High-dimensional statistics (anglais) - [30h Projet] | B1 | Q1 | 30 | 15 | [+] | 5 |
| INFO8010-1 | Deep learning (anglais) - [60h Projet] | B1 | Q2 | 30 | - | [+] | 5 |
| INFO9014-1 | Knowledge representation and reasoning (anglais) - [45h Projet] | B1 | Q2 | 24 | 20 | [+] | 5 |
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Optional courses
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