2 refresher courses to take based on the student’s academic background
Refresher courses
- Statistical modelling (2 ects)
- Algorithms and programming (2 ects)
- Basics of exercice physiology and biomechanics (2 ects)
- Scientific basis of physical preparation (2 ects)
Mandatory core courses
Core courses
- Biomechanics of human movement (3 ects)
- Integrative exercise physiology (3 ects)
- Databases (3 ects)
- Data visualisation(2 ects)
- Sport in the digital age (2 ects)
- Professional interaction
- French (3 ects)
1 course to choose from the following minors + 1 optional elective course
Minors
Sport sciences
- Methodology for the optimization of training and physical preparation (4 ects)
- Physiology and biomechanics for the athlete’s analysis (4 ects)
- Psychosocial processes and physical behavior (4 ects)
- Sensors and evaluation of physical behavior (4 ects)
Electronics
- Sensors and instrumentation (4 ects)
It is recommended to choose this course in order to follow the “Metrology of human movement and innovative sensors” during the 2nd semester
Computer science
- Introduction to virtual reality (4 ects)
It is recommended to choose this course in order to follow the “Digital solutions for interaction in sport” during the 2nd semester
Data science
- Linear models (4 ects)
- Supervised learning (4 ects)
These courses are delivered by the ENSAI and require an advanced level in data science
1 research project to undetake during the year
Project
Interdisciplinary research project in group (6 ects)
Core courses
Core courses are mandatory for all students involved in the “Digital science and Sport” master.
It includes all the fundamentals of the training program.
Minor
Minor courses enable the acquisition of complementary skills in another field and allow students to build a unique profile tailored to their aspirations and competences.
Students must choose 1 minor course during the 1st semester. A second optional course can also be followed.
Project
Through the project course, students will develop their research, interdisciplinarity and collaboration skills.
Semester 2 (M1)
Core courses
- Methods and instruments for the assessment of sports performance (3 ects)
- Modeling and simulation of movement (3 ects)
- Tutoring (3 ects)
- Professional interaction (2 ects)
- French (3 ects)
1 major to elect
Metrology of human movement and innovative sensors Major
- Sensors and instrumentation level 2 (3 ects)
To choose this course, it is recommended for the student to have followed the “Sensors and instrumentation” course during the 1st Semester or to have sufficient knowledge in electronics to meet the course requirements
- Modeling and simulation of movement level 2 (3 ects)
Digital solutions for interaction in sport Major
- C++ programming (3 ects)
- Software engineering (3 ects)
To choose this major, it is recommended for the student to have followed the “introduction to virtual reality” course during the 1st Semester or to have sufficient knowledge in computer science
Analysis, modeling and simulation of movement Major
- Modeling and simulation of movement level (3 ects)
- Biomechanics of human movement level 2 (3 ects)
Data science applied to sport Major
- Data mining (3 ects)
One of the following :
- Movement efficiency (3 ects)
- Duration models (3 ects)
An advanced level in data sciences is required to follow the “Duration models” course
3 minor courses to choose + 1 optional course
Minor
Sport science
- Methodology of training and physical preparation (3 ects)
- Movement efficiency (3 ects)
- Training ingineering (3 ects)
Electronics
- Sensors and instrumentation level 2 (3 ects)
To choose this course, it is recommended for the student to have followed the “Sensors and instrumentation” course during the 1st Semester or to have sufficient knowledge in electronics to meet the course requirements
Computer science
- C++ programming (3 ects)
To choose this course, it is recommended for the student to have followed the “Introduction to virtual reality” course during the 1st Semester or to have sufficient knowledge in computer science to meet the course requirements
- Software engineering (3 ects)
To choose this course, the student must follow the “C++ programming” course or to have sufficient knowledge in electronics to meet the course requirements
Data science
- Data mining (3 ects)
- Duration models (3 ects)
To choose this course, the student must follow the “Data mining” course or to have sufficient knowledge in data science to meet the course requirements
Modeling
- Modeling and simulation of movement level 2 (3 ects)
Research project
Project
Interdisciplinary research project in group (1 ects)
Core courses
Core courses are mandatory for all students involved in the “Digital science and Sport” master.
It includes all the fundamentals of the training program.
Major
The major includes specialisation courses to choose according to the student’s targeted work profile.
Minor
Minor courses enable the acquisition of complementary skills in another field and allow students to build a unique profile tailored to their aspirations and competences.
Students must choose 3 minor courses during the 2nd semester. A fourth optional course can also be followed.
Projet
Through the project course, students will develop their research, interdisciplinarity and collaboration skills.
Semester 3 (M2)
Core courses
- Digital tools and monitoring of training load (3.5 ects)
- Research methodology(3.5 ects)
- Seminars/conferences (2 ects)
Metrology of human movement and innovative sensors Major
- Emerging technologies for performance (3 ects)
- Sensors and instrumentation level 3 (3 ects)
- Ingénierie de la conception (3 ects)
Digital solutions for interaction in sport Major
- Data mining and clustering (3 ects)
It is recommended for the student to have followed the “Data mining” course during the 2nd semester or to have sufficient knowledge in data science to meet the course requirements
- Computer science complementary skills 1 (3 ects)
- Computer science complementary skills 2 (3 ects)
Analysis, modeling and simulation of movement Major
- Emerging technologies for performance (3 ects)
- Cosimulation humain-système (3 ects)
One of the following :
- Physiology and biomechanics for the athlete’s analysis (3 ects)
- Sensors and instrumentation level 3
To choose this course, it is recommended for the student to have follow the “Sensors and instrumentation level 1 and level 2” during the 1st year or the have sufficient knowledge in electronics to meet the course requirements
Data science applied to sport Major
- Data mining & clustering (3 ects)
It is recommended for the student to have followed the “Data mining” course during the 2nd semester or to have sufficient knowledge in data science to meet the course requirements
- Statistical learning (3 ects)
- Deep learning (3 ects)
2 minor course to choose + 1 optional elective course to choose from the minor courses of the 1st semester
Minor
Sport science
- Fatigue and recovery strategies (3 ects)
- Optimisation of training and physical preparation (3 ects)
- Physiology and biomechanics for the athlete’s analysis (3 ects)
- Psychosocial processes and and physical activity (3 ects)
- Sensors and evaluation of physical behavior (3 ects)
Electronics
- Sensors and instrumentation level 3 (3 ects)
- Ingénierie de la conception (3 ects)
- Sensors and instrumentation level 1 (3 ects)
Computer science
- Computer science complementary skills 1 (3 ects)
- Computer science complementary skills 2 (3 ects)
- Introduction to virtual reality (3 ects)
Data science
- Statistical learning (3 ects)
- Deep learning (3 ects)
- Data mining et clustering (3 ects)
- Linear models (3 ects)
- Supervised learning (3 ects)
Modeling
- Co-simulation humain-système (3 ects)
Research project
Project
Interdisciplinary research project in group (4 ects)
Core courses
Core courses are mandatory for all students involved in the “Digital science and Sport” master.
It includes all the fundamentals of the training program.
Major
The major includes specialisation courses to choose according to the student’s targeted work profile.
Minor
Minor courses enable the acquisition of complementary skills in another field and allow students to build a unique profile tailored to their aspirations and competences.
Students must choose 2 minor courses during the 3rd semester. A third optional course can also be followed.
Project
Through the project course, students will develop their research, interdisciplinarity and collaboration skills.
Semester 4 (M2)
Internship
- internship in a company or laboratory (30 ects)
Students can choose to follow one optional course from the courses of the 2nd semester
Minor
Sport science
- Methodology of training and physical preparation (3 ects)
- Movement efficiency (3 ects)
- Training engineering (3 ects)
Electronics
- Sensors and instrumentation level 2 (3 ects)
Computer science
- C++ Programming (3 ects)
- Software ingineering (3 ects)
Data science
- Data mining (3 ects)
- Duration models (3 ects)
Modeling
- Modeling and simulation of movement level 2 (3 ects)
Internship
During the 4th semester, students must accomplish a 4 to 6-month internship in a company or laboratory.
Mineure
Minor courses enable the acquisition of complementary skills in another field and allow students to build a unique profile tailored to their aspirations and competences.
Students can choose 1 minor course during the 4th semester (optional).
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