The Health-AI Master 2 is a 1 year master degree (60 ECTS), fully taught in English , and coordinated by the University of Bourgogne (uB, France).

The Master is structured in two semesters:

• A first semester dedicated to methodology courses with a main focus on AI applications for Health. This semester bridges skills and competences from Computer Science and Image Processing/Signal Processing fields.
• A second semester in which students develop their Master thesis at the University of Burgundy or collaborating institutions (research centers, universities or companies) working in the field of Medical imaging and its applications.

In summary, the acquired knowledge and transversal competences will be very important assets for the students for their future employability and career prospects, as those are aspects that companies and research institutions value in recent graduates.

The master is designed for students holding a degree in Computer Science, Electronics/Signal Processing or in Health (with some knowledge in Computer Science and high motivations towards Artificial Intelligence):

• An equivalent to a M1 master (240 ECTS) from a French higher education university,
• A four years degree or fast-track programme equivalent to 240 ECTS from a Foreign education system.

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During the first semester, students attend advanced courses on Computer Science, Image/Signal Processing for AI-based Health applications, including Medical Imaging, Image Processing, Machine learning and Deep Learning, ...

The second semester is dedicated to the Master thesis carried out within any academic or industrial laboratory.

Our programme is designed to offer students solid scientific foundations, in order to take part in the growing area of Artificial Intelligence for Health.

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For students coming outside Health sector

• Fundamental concepts: X-ray and g-ray physics applied in medicine, Ultrasound and Doppler effect, Spin physics and basic imaging concepts,
• Introduction to DICOM format
• Introduction to imaging reconstruction: projections, filtered back-projection, Fast Fourier Transform
• Magnetic Resonance Imaging: Advanced technical considerations, Segmented k-space, Echo-Planar Imaging, Parallel Imaging
• Advanced imaging techniques in medicine: Angiography, Flow Quantification, Diffusion and Perfusion
• Other "imaging" techniques: EEG, fNIRS
• ...

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For students coming from Health Sector

• Introduction to Python and Computer Programming
• Data Types, Variables, Basic Input-Output Operations, Basic Operators
• Boolean Values, Conditional Execution, Loops, Lists and List Processing, Logical and Bitwise Operations
• Functions, Tuples, Dictionaries, and Data Processing
• Modules, Packages, String and List Methods, and Exceptions
• The Object-Oriented Approach: Classes, Methods, Objects, and the Standard Objective Features; Exception Handling, and Working with Files Numpy, Pandas, ...
• ...

• Introduction to digital image processing,
• Signals in 2 and more dimensions,
• Image enhancement,
• Image segmentation,
• Image registration,
• ...

• Bayes decision theory,
• Parametric and non-parametric classification,
• Feature selection and extraction,
• Margins and Kernel based algorithms,
• Ensemble classification and learning,
• Deep learning: CNNs, RNNs, GANs,
• ...

• Cloud Computing:
  • History: going beyond virtualization
  • Types of cloud computing: private, hosted, public and hybrid
  • Cloud service models: SaaS, PaaS and IaaS
  • Cloud computing concepts: virtualization, service-oriented architectures (SOA) and Web services
  • Cloud subscription types: from mainframe to cloud
  • Usages of cloud computing: actors, services, deployment examples
  • Cloud architectures: N-tier, SOA and multi-tenancy
  • Application scaling: monoliths, microservices, serverless
  • Implementation approaches: DevOps, CI/CD, containers (Docker, Kubernetes)
• Cybersecurity:
  • Breaches, threats, vulnerabilities
  • Security principles: authentication, authorisation, minimum privileges, non-repudiation
  • Risks: state of the art of vulnerabilities and threats, black clouds
  • Security breaches: anatomy, DoS attack analysis
  • Security standards: ITIL, ISO 27000
  • Securing accesses: authentication protocols (Kerberos, SAP, ICP), access control
  • Securing data: integrity, confidentiality, availability
  • Cryptography: approaches and algorithms (public key certificates, digital signature, time-stamping, anonymity)
• AI for Cybersecurity
  • Python libraries for AI and cybersecurity: NumPy, Scikit-learn, Matplotlib, Seaborn, Pandas, Pefile, Volatility
  • Detecting Email Cybersecurity Threats with AI
  • Malware Threat Detection
  • Network Anomaly Detection with AI: classify network attacks, detect botnet topology

• Introduction
• Knowledge Engineering
• MultiAgents Systems
• Data Science
• Expert Systems
• ...

Applications are open to well-trained students from all around the world who have completed 4 consecutive years (or fast-track) of higher education, equivalent to 240 ECTS credits, in a relevant field, such as Computer Science, Electronics/Signal Processing or in Health (with some knowledge in Computer Science and high motivations towards Artificial Intelligence).

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a) Procedure for EU or non-EU applicants who have not completed one year of a French national university degree

Procedure and timetable to follow : https://en.u-bourgogne.fr/admission/degree-seeking-students.html

• For candidates from Country with the "Etudes en France" procedure: Candidates should create their Studying in France personal on-line account right away. Studying in France application period: October 1, 2022 – December 15, 2022 (check dates on website).
• For candidates from countries without "Etudes en France" procedure: Candidates have to fill in the online form: application form for ENGLISH-taught programmes; (Deadline for non-EU candidates January 1, 2023, deadline for EU-candidates March 31, 2023).

b) Procedure for applicants who already have a French diploma, which gives them access to this study programme.

Candidates have to apply using ecandidat platform (open between March and June 15, 2023).

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Responsable de formation :

Stéphanie Bricq stephanie.bricq@u-bourgogne.fr

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Responsable du master informatique :

Nadine Cullot nadine.cullot@u-bourgogne.fr

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Scolarité :

Véronique Magnin veronique.magnin@u-bourgogne.fr

03.80.39.59.87

Département I.E.M - U.F.R. Sciences et Techniques - B.P. 47870 – 21078 Dijon Cedex

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