Program

Structure

Modules Artificial Intelligence, Medicine and Applications

In the first semester, students have to register for the following mandatory courses from the modules Artificial Intelligence, Medicine and Applications:

Artificial Intelligence (AI)
 Mandatory Courses

Introduction to Artificial Intelligence

 5 ECTS

Machine Learning

 5 ECTS
Medicine
 Mandatory Courses

Basics in Physiology

 3 ECTS

Introduction to Clinics

 4 ECTS
Applications
 Mandatory Courses

Computer Vision

 5 ECTS

Introduction to Digital Signal Processing

 3 ECTS

Module Foundation / Electives

The selection of courses from the module Foundation depends on the students' individual scientific background, from the module Electives on the students' interests.

Students may only consider courses in the selection below. Should you wish to take a course outside of the selection, please contact the study coordination and Professor Mougiakakou for an assessment of the course. 

Foundation / Electives
 Non-Mandatory Courses / Pool of Courses

Foundation

Applied Biostatics with Practicals I

 4 ECTS

Applied Optimization

 5 ECTS

Discrete Mathematics

 5 ECTS

HPC and Cloud Computing

 1 ECTS

Internet of Things

 5 ECTS

Introduction to Programming

 2 ECTS

Introduction to Python

 2 ECTS

Linear Models and Regression I

 9 ECTS

Numerical Methods

 5 ECTS

Selected Chapters in Mathematics

 2 ECTS

Seminar in Data Science

 5 ECTS

Electives


 none

Modules Artificial Intelligence, Medicine and Applications

In the second semester, students have to register for the following mandatory courses from the modules Artificial Intelligence, Medicine and Applications:

Artificial Intelligence (AI)
 Mandatory Courses

Deep Learning

 5 ECTS
Medicine
 Mandatory Courses

Clinical Implementations of AI

 4 ECTS
Applications
 Mandatory Courses

Clinical Decision Support

 3 ECTS

AI for Medical Time Series Data (replaced by Trustworthy AI in Medicine for 2025)

 3 ECTS

Trustworthy AI in Medicine (2025 only)

 3 ECTS

Module Foundation / Electives

The selection of courses from the module Foundation depends on the students' individual scientific background, from the module Electives on the students' interests.

Students may only consider courses in the selection below. Should you wish to take a course outside of the selection, please contact the study coordination and Professor Mougiakakou for an assessment of the course. 

Foundation / Electives

Foundations

3D Geometry Processing

 5 ECTS

Algorithms, Probability and Information

 5 ECTS

Applied Biostatistics II. with Practicals

 4 ECTS

C++ Programming I 

 3 ECTS

Data Structures and Algorithms (in German)

 5 ECTS

Ethical and Legal Issues (can also be an elective)

 3 ECTS

Graph-based Pattern Recognition

 5 ECTS

Introduction to Medical Statistics

 3 ECTS

Seminar Applied Optimisation 

 5 ECTS

Seminar in Cryptography and Data Security

 5 ECTS

Seminar Machine Learning and Artificial Intelligence

 5 ECTS

Electives

Advanced Networking and Future Internet

 5 ECTS

Biomedical Sensors

 3 ECTS

Biomedical Signal Processing and Analysis

 3 ECTS

Clinical Epidemiology and Health Technology Assessment

 2 ECTS

Computer-Assisted Surgery

 3 ECTS

Databases (in German)

 5 ECTS

Finite Element Analysis I

 3 ECTS

Fundamentals of Quality Management and Regulatory Affairs

 4 ECTS

Introduction Image Analysis

 3 ECTS

Introduction to Precision Medicine

 3 ECTS

Medical Robotics 

 3 ECTS

Microsystems Engineering

 3 ECTS

Proteomics & Metabolomics (lecture and practicals)

 5 ECTS

Regenerative Dentistry for Biomedical Engineering

 2 ECTS

Rehabilitation Technology

 3 ECTS

Seminar Explainable AI - Human Computer Interaction meets Artificial Intelligence

 5 ECTS

Seminar Life Engineering 

 5 ECTS

Modules Artificial Intelligence, Medicine and Applications

In the third semester, students have to register for the following mandatory courses from the modules Artificial Intelligence, Medicine and Applications:

Artificial Intelligence (AI)
 Mandatory Courses

Reinforcement Learning 

 5 ECTS
Medicine
 Mandatory Courses

Clinical Implementations of AI II

 4 ECTS

Omics for Non-Biologists

 3 ECTS
Applications
 Mandatory Courses

Medical Image Analysis

 3 ECTS

From NLP to LLMs

 3 ECTS

Module Foundation / Electives

The selection of courses from the module Foundation depends on the students' individual scientific background, from the module Electives on the students' interests.

Students may only consider courses in the selection below. Should you wish to take a course outside of the selection, please contact the study coordination and Professor Mougiakakou for an assessment of the course. 

Foundation / Electives

Foundations

Applied Optimization

 5 ECTS

Computer Graphics

 5 ECTS

HPC and Cloud Computing 

 1 ECTS

Internet of Things

 5 ECTS

Linear Models and Regression I 

 9 ECTS

Medical Informatics

 3 ECTS

Seminar Data Science

 5 ECTS

Seminar in Cryptography and Data Security

 5 ECTS

Seminar Machine Learning and Artificial Intelligence

 5 ECTS


Electives

Advanced Medical Statistics

 3 ECTS

Cardiovascular Technology

 3 ECTS

Computational Epidemiology

 1.5 ECTS

Computer Graphics & Geometry Processing

 5 ECTS

Data Driven Diabetes Management

 3 ECTS

Design of Clinical Trials

 3 ECTS

Digital Sustainability

 1 ECTS

Foundations of Deep Learning

 6 ECTS

Health Insurance

 3 ECTS

Health Law (in German)

 5 ECTS

Innovation Management

 2 ECTS

Intelligent Implants and Surgical Instruments

 3 ECTS

Medical Image Analysis Lab

 4 ECTS

Modeling and Scaling of Generative AI Systems

 5 ECTS

Molecular Biology and Genetics for Non-Biologists (Lecture)

 3 ECTS

Neurotechnology 

 3 ECTS

Ophtalmic Technologies

 3 ECTS

Principles of Medical Imaging

 3 ECTS

Programming of Mircrocontrollers

 5 ECTS

Seminar Generative AI

 5 ECTS

Seminar Life Engineering

 5 ECTS

Seminar Trustworthy AI models and systems

 5 ECTS

Seminar Handling Health Data (Generative) AI in Healthcare (in German)

 5 ECTS

The 4th semester is reserved for the master's thesis. You can find more information in the following link.

Most of our students study full-time and work at the same time. We support them and organize mandatory courses on three days of the week only.

Students who work may officially request to extend their studies to six semesters.

Interested in finding a job in the industry? Then the University of Bern is the place to be! There are around 280 medical technology manufacturers and suppliers in the canton of Bern and the sector is constantly growing, with the number of jobs in medical technology rising. (Source: Swiss Medtech (Network) Bern Economic Development Agency)

Our 12 different research groups at the ARTORG Center offer part-time jobs to excellent students. If you are interested please contact the individual research groups. 

 

 

Do you want to brush up on your maths before the start of the program?

The preparation week provides an opportunity for students to work on their skills and be prepared for the master's program Artificial Intelligence in Medicine at the University of Bern.

By combining theoretical lectures on linear algebra, optimization and probability with a rich array of practical exercises in Python, MSc AIM's fall session will successfully prepare you for the new and exciting challenges!

2025 preparation week:

  • 8th September: Linear Algebra (class 9h-12h, practical 14h-17h)
  • 9th September: Linear Algebra (class 9h-12h, practical 14h-17h)
  • 10th September: Probability (class 9h-12h, practical 14h-17h)
  • 11th September: Optimisation (class 9h-12h, practical 14h-17h)
  • 12th September: 9:30-11h Welcome Event followed by "Cafe und Gipfeli"

The preparation week will take place in Hörraum F-105 in Unitobler. The building adresse is Lerchenweg 36, 3012 Bern. 

Alongside the AIM preparation week, the university organises the "Tag des Studienbeginns" on the 12th of September. The day includes a few talks from the faculty of medicine and a freshers fair with student clubs of the university. More information can be found on the university website.

Click here to view the week in KSL

Registration to preparation week 2025 and welcome event

Students with disabilities or chronic illnesses have a right to Access Arrangements. 

Please refer to the university page for the procedure to follow to obtain the arrangement required.