Course Information

About this course

Artificial Neural Networks are programs that write themselves when given an objective, some training data, and abundant computing power. Recently, these programs have brought about a wide array of impressive innovations, such as self-driving cars, face recognition, and human-like speech generators. This course offers you an introduction to Deep Artificial Neural Networks (i.e. “Deep Learning”). With focus on both theory and practice, we cover models for various applications, how they are trained and tested, and how they can be deployed in real-world applications

Syllabus

Spring 2026 – Section A

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Spring 2026 – Section B

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Spring 2026 – Section C

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Spring 2026 – Section D

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Pre-requisites

One year of computer science at university level. One of the computer science courses should be in algorithms and data structures. One course in either probability theory, linear algebra, or statistics at university level. Knowledge of at least one object-oriented programming language (e.g. Java, Python).

Travel on Study Tour

You only take one Core Course per semester, and each Core Course includes two Study Tours: one Short Study Tour to a nearby destination for three days, and one Long Study Tour to another European country for six days.

Led by your faculty, Study Tours take you into real-world settings where you will apply what you’ve learned outside the classroom.

Check out the Study Tours for this course
Students sitting on the floor in a modern building, engaging in a group activity with papers and notebooks scattered around.

Faculty

Iraklis Moutidis

Ph.D. in Computer Science (Natural Language Processing and Social Network Analysis), University of Exeter (2023). Currently working on Natural Language and Machine Learning projects as a Freelance Data Scientist (2021–present). Previously built engineering-related applications as Software Developer at Moduleering CAE Greece (2017) and implemented simulations for the 100Gbits/sec technology hardware as a Summer Student at CERN (2016). With DIS since 2025.

Lucian Leahu

Ph.D. in Computer Science, Cornell University (2012). Previous experience as Assistant Professor at ITU Copenhagen (2015-2018), ERCIM Postdoctoral Fellow at the Swedish Institute of Computer Science (2012-2013), and Project Leader in the Media Technology and Interaction Design Department at the Royal Institute of Technology (2014). With DIS since 2019.

Lorenzo Belgrano

M.Sc. in Mathematical Modelling and Computation, Technical University of Denmark (2019). B.Sc. in Information Engineering, University of Padua (2016). Senior Machine Learning Engineer at Corti (2019–2024). Previous experience implementing deployment pipelines using Docker and Azure ML and developed a FastAPI to request detection to ML models using Tensorflow Serving. With DIS since 2023.

Matthias Heumesser

Ph.D. in Atmospheric Physics, Marie Skłodowska-Curie Fellow, Technical University of Denmark (2021). Machine Learning Engineer at Vestas (2024–present). Previously led development of custom car and charger integrations for a smart charging platform as Development Team Lead at True Energy A/S (2022–2024). Previous experience developing NLP models for question and implied information detection in emergency calls as Software Developer at Corti (2021–2022). With DIS since 2023. 

Long study tour

About this tour

London is one of the most technologically advanced cities in the world, exemplified with East London Tech City, also known as Silicon Roundabout. You will gain an understanding of the myriads of possibilities for trained data scientists by visiting companies relying on deep learning and neural networks – whether it being small start-ups or established giants in the marked. You will get an international view of the future of AI research by engaging with researchers and students at London high profile computer science institutions.

A Study Tour to London would not be complete without a chance to experience its cultural and ethnic diversity. Through touring boroughs, exploring significant sites, and visiting museums, you will learn about the historic and contemporary United Kingdom.

Learning outcomes

  • Learn about how deep learning and data science are used in industry and academic research

  • Understand how people coming from different backgrounds work with machine learning and AI
  • Engage in your personal learning process outside the classroom by actively participating and challenging your current beliefs, ideas, and assumptions
  • Get to know your fellow students and professor in an educational and social setting outside DIS

Possible activities

  • Meet with professionals working in tech giants or tech start-ups based in London

  • Tour Tech City to understand what it takes to create a tech cluster – or simply what it takes to start up yourself
  • Learn from researchers and peers within London’s prime computer science institutions such as Imperial College, Cambridge, or Kings College

London

About this tour

With specialized education, strong support and funding, and cutting-edge research, Sweden is one of the most technologically advanced countries in the world, and a growing center for artificial intelligence and deep learning. Through visiting Stockholm, Sweden’s capital, you will learn about current applications of artificial intelligence in various fields, such as business intelligence, healthcare, life sciences, autonomous driving, and mobility. Through visiting startups, large companies, and research institutions currently driving innovations in machine learning and deep learning, you will gain an understanding of the necessity, utility, and impact that this field is having in a wide variety of sectors.

Learning outcomes

  • Broaden your perspective of artificial neural networks in a European context through visits to firms, while assessing affordances and limitations of incorporating deep learning approaches in various sectors

  • Gain an understanding of the dynamic interplay between research, development, industry, and everyday applications through conversations with deep learning experts

  • Challenge your current ideas and assumptions of the field and provide opportunities for you to direct your own learning process outside the classroom

Possible activities

  • Meet professionals working in industry, from start-ups to Swedish tech giants

  • Learn from computer science researchers at Sweden’s leading academic institutions, such as the Royal Institute of Technology

  • Visit CAI (Center for AI, Innovation and the Future of Work)

Stockholm Sweden

About this tour

Germany is one of the most technologically advanced countries in the world, boasting specialized tech education opportunities, strong governmental support and funding for industry, and cutting-edge research in the field of AI. Germany’s capital, Berlin, is increasingly growing as a center for artificial intelligence and deep learning, with current applications in business intelligence, healthcare, life sciences, autonomous driving, and mobility.

In Berlin, you will visit professionals working in industry, from start-ups to large tech giants, to hear how they are applying AI in their respective sectors. At research institutions, you will hear from the researchers currently driving innovations in the field of machine learning. Throughout the week you will develop your understanding of the necessity, utility, and impact that machine learning is having across German society.

Learning outcomes

  • Broaden your perspective of artificial neural networks in a European context through visits to firms, while assessing affordances and limitations of incorporating deep learning approaches in various sectors

  • Gain an understanding of the dynamic interplay between research, development, industry, and everyday applications through conversations with deep learning experts
  • Challenge your current ideas and assumptions of the field and provide opportunities for you to direct your own learning process outside the classroom

Possible activities

  • Meet professionals working in industry, from start-ups to German tech giants

  • Learn from researchers within Germany’s premier computer science academic institutions, such as the Technical University of Munich or the Technical University of Berlin
  • Visit BIFOLD (Berlin Institute for the Foundations of Learning and Data)

Berlin
Copenhagen

Short study tour

About this tour

Alongside a two-day seminar in Copenhagen, you will travel on a three-day Study Tour in Denmark to gain insight into the field of artificial neural networks and deep learning by meeting various professionals in both the educational and industry setting. You will have the opportunity to discuss and understand the challenges of the field and hear from the experiences of developers. You will visit both industry and academic institutions involved in both models- and real-world applications of artificial neural network programs. See how what we have learned in class about propagation, model-fitting, pattern recognition and prediction and more come to live in solutions already put to use today as well as what is in the pipeline for AI in the not so distant future.

The program is supplemented with cultural visits to help you learn more about Danish history and culture and experience life outside the capital. Some cultural visits include touring art museums, visiting historical sites, and enjoying traditional Danish food.

Learning outcomes

  • Gain insight to the translation of computer science from academia to industry

  • Understand the computer programming techniques that are most heavily involved within the profession

  • Engage in your personal learning process outside the classroom by actively participating and challenging your current ideas and assumptions.

  • Get to know your fellow students and professor in an educational and social setting outside DIS

Possible activities

  • Learn how AI are at the core of security solutions at specialized tech companies like Therma in Århus

  • Visit Odense Robitics – a high-tech cluster of robot and automation companies

  • Meet with peers and professors at the DataLab at Århus University