Composante
UFR Sciences et Techniques
Langue(s) d'enseignement
Anglais
Présentation
Presentation:
The Health and Artificial Intelligence track is one of the four tracks of the Master’s degree in Computer Science. It adopts a multidisciplinary approach at the intersection of computer science, artificial intelligence, and the healthcare domain.
25 étudiants
Capacité d'accueil globale
Objectifs
Objectives:
The objective of the Health and Artificial Intelligence track is to train specialists capable of designing, developing, and mastering artificial intelligence applications dedicated to the healthcare domain, covering the entire pipeline from data collection and management to data processing, analysis, and valorization.
Upon completion of the programme, students will have acquired solid fundamental and methodological knowledge in artificial intelligence, data science, and computer science, enabling them to apply approaches tailored to the specific characteristics of healthcare data. They will master the main machine learning and deep learning techniques, as well as methods for processing structured data, signals, and medical images.
Students will also develop practical skills in the design and implementation of software solutions integrating AI models, while taking into account constraints specific to the healthcare domain, such as data quality and heterogeneity, as well as ethical, regulatory, and societal issues.
Compétences acquises
Acquired skills:
- Analyze a healthcare need and identify the relevant data required to address a given problem.
- Collect, structure, and prepare healthcare data, taking into account data quality as well as regulatory and ethical constraints.Model a healthcare problem using artificial intelligence methods adapted to the characteristics of the data being processed.
- Develop and integrate software solutions leveraging artificial intelligence models for the processing of healthcare data, signals, or medical images.
- Present, interpret, and add value to results for both specialized and non-specialized audiences, within an interdisciplinary context.
Organisation
Contrôle des connaissances
- Assessment methods:
Knowledge is assessed and examinations are conducted in accordance with the Common Framework for Studies adopted on December 18, 2023 by the Board of Directors of the University of Burgundy.
- Compensation rule:
Compensation applies between semesters of the same academic year. - Repeating a year:
Repeating a year is not automatic and is subject to the decision of the examination board. In accordance with the Common Framework for Studies of UBE, student engagement may be recognized, following discussion at the very beginning of the semester with the program coordinator, who will then specify the applicable arrangements. The examination board will take this engagement into account in the form of a bonus applied to the semester average, which may amount to up to 0.2 points.
Stages
Intitulé | Master 2 : Mandatory internship from March to September |
|---|---|
Durée | 670h min |
Programme
Sélectionnez un programme
Master 1
UE1 Discrete Mathematics an Statistics for Data Analysis
5 créditsUE2 Medical Signal and Image Processing
5 créditsUE3 IOT and Applications for Healthcare
5 créditsUE4 Law and Regulations
5 créditsUE5 Fundamentals of Programming
5 créditsUE6 Databases
5 créditsUE7 Medical Imaging
5 créditsUE 8 Medical Knowledge A
5 crédits
UE 9 Medical Law and Ethics
4 créditsUE 10 Project Management
5 créditsUE 11 Machine Learning Methods
5 créditsUE 12 Distributed AI and multi-agent systems
4 créditsUE 13 Health Data Analysis
4 créditsUE 14 Medical Knowledge B
4 créditsUE 15 Medical Knowledge C
4 crédits
Master 2
UE annuelles obligatoires
UE3 - Image Processing
6 créditsUE4 - Cloud Computing and Cybersecurity
6 créditsUE5 - Hybrid and Distributed AI
6 créditsUE6 - Projet Tuteuré
6 créditsUE7 - Machine Learning and Deep Learning
6 créditsUE8 - Stage
24 crédits
UE annuelles à choix
Au choix : 1 parmi 1
UE annuelles à choix (1 parmi 2)
Au choix : 1 parmi 2
Admission
Conditions d'accès
Admission requirements Master 1:
Applications are submitted via the MonMaster portal for domestic students or those who have already completed at least one year of study in France, and via the Campus France portal for international applicants.
Master 2 :
Ecandidat :https://ecandidat.ube.fr/ecandidat/stylesheets/cas/accueil.faces#!accueilView and via the Campus France portal for international applicants.
Modalités de candidatures
Application procedures Master 1 :
Applications must be submitted via the MonMaster portal or, for international applicants, through the Campus France portal. Applications are then reviewed by an academic admissions committee. (https://monmaster.gouv.fr/formation)
Master 2 :
Ecandidat :https://ecandidat.ube.fr/ecandidat/stylesheets/cas/accueil.faces#!accueilView and via the Campus France portal for international applicants.
Attendus / Pré-requis
Recommended prerequisites:
- Hold a qualification equivalent to a Bachelor’s degree (three years of higher education).
- Develop a structured and critical argumentation.
- Apply reasoned approaches to problem solving.
- Use standard digital tools and apply information security rules.
- Exploit data acquisition and data analysis software with a critical approach.
- Communicate in English, both orally and in writing, in a scientific context.
Pré-requis recommandés
Recommended prerequisites:
Bachelor’s degree in Computer Science or equivalent for students from a computer science background; Bachelor’s degree in Bioinformatics; Bachelor’s degree in Health Sciences for students from a health-related background.
Et après
Poursuite d'études
Further studies : Master 2 in Health and Artificial Intelligence
Possibility of continuing on to a doctorate after the M2.
Débouchés professionnels
Career opportunities:
after the Master’s degree in Health and Artificial Intelligence are numerous and span a wide range of sectors, including large digital and healthcare companies, hospitals and clinics, public and private research laboratories, as well as SMEs and start-ups developing artificial intelligence solutions for the healthcare domain.
Graduates may pursue positions such as artificial intelligence engineer, digital health engineer, AI project or study officer in healthcare, or research engineer, working within multidisciplinary teams that bring together computer scientists, physicians, and healthcare professionals.