Deep Learning with Applications in Medical Imaging 7.5 credits

About the course

This course covers deep convolutional neural networks (CNNs) for computer vision, with applications in medical image analysis. The course provides an introduction to fundamental concepts in machine learning, describes neural networks and the field of deep learning, and goes into detail about deep CNNs. The course describes the different parts that are used when building deep CNNs, such as filters, activation functions, loss functions; regularization techniques such as e.g. batch normalization and dropout; explains several of the different non-linear optimization algorithms that are used when training the networks, and describes popular network architectures, and discusses their pros and cons. The course also covers generative models, such as variational autoencoders (VAE) and generative adversarial networks (GANs).

Students in this course will learn to implement and train modern network architectures and deep learning methods, and apply these to large image datasets with medical and other images.

The course has two modules:
Theory and method, 5.5 ECTS credits
Practical assignments, 2.0 ECTS credits

Show syllabus

Apply

Spring 2026
- Deep Learning with Applications in Medical Imaging
  
  Second admissions round for EU/EEA citizens
  
  VT26 / Umeå / English / On site
  
  Submit a late application
  
  Show more Show less
  
  Starts
  24 March 2026
  
  Ends
  7 June 2026
  
  Number of credits
  7.5 credits
  
  Type of studies
  On site
  
  Study pace
  50%
  
  Teaching hours
  Daytime
  
  Study location
  Umeå
  
  Language
  English
  
  Application code
  UMU-31008
  
  Eligibility
  
  Univ: For access to the course requires 90 credits of completed studies in one of the main areas of computer science, physics, electronics, chemistry, mathematics or mathematical statistics are required, or 2 years of completed studies (120 credits). Of these credits, at least 7.5 credits are required in basic programming methodology in Python, C, and/or Matlab, at least 7.5 credits dealing with Data Structures and Algorithms, at least 7.5 credits dealing with Linear Algebra, at least 7.5 credits dealing with analysis with concepts such as derivatives and limit values, at least 7.5 credits dealing with mathematical statistics, or equivalent knowledge. Proficiency in English equivalent to the level required for basic eligibility for higher studies if the teacing language is english.
  
  Selection
  
  Academic credits awarded by application deadline (HPAV 30-285 ECTS)
  
  Application
  Application deadline was 15 October 2025. Please note: This second application round is intended only for EU/EEA/Swiss citizens. Submit a late application at Universityadmissions.se.
  
  Application and tuition fees
  As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.
  
  Application fee: SEK 900
  
  Tuition fee, first instalment: SEK 20,800
  
  Total fee: SEK 20,800
  
  Details about tuition, fees and funding

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