Deep Learning

  • This programme is taught in English
  • This Programme is offered in Odense

Computer science forms the basis for development of efficient and secure modern software, and computer scientists excel at working at all levels from program developers to project managers and executives in software divisions and  software companies.

Come and join the summer course “Deep learning” at SDU. Machine learning has become a part in our everyday life, from simple product recommendations to personal electronic assistant to self-driving cars. Especially deep learning has gained a lot of interest in the media and has demonstrated impressive results. This intensive course will introduce you to the exciting world of deep learning. We will learn about the theoretical background and concepts driving deep learning and highlight and discuss the most noteworthy applications of deep learning but also their limitations. Furthermore you will also apply and implement your first deep neural networks in order to solve various interesting machine learning tasks.

The course is run by Department of Mathematics and Computer Science. The research of the department covers a broad area, is interdisciplinary and includes both pure and applied research. Computer science research topics include algorithmics, formal methods and programming languages, optimization, data mining, machine learning, bioinformatics and cheminformatics. The department offers high quality study programmes in computer science at both Bachelor and Master level. All courses on the Master level are offered in English.

Teaching and Instruction method

The course will consist of lectures, exercise sessions, and programming sessions. The evaluation will be a written exam.  Grading according to the Danish 7-point scale.

Required skills

You must have completed at least two years of studies within computer science or related studies. Familiarity with Python programming is assumed.

Related degrees

MSc in Computer Science
MSc in Software Engineering

Course description

See the course description.

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