Computer Science
Computing is everywhere. It advances science and industry, helps us stay connected, and affects our lives at individual and societal levels. Denmark invests heavily in computing, with specialized educations, public funds for tech startups, and industrial hubs that place computer science at their core making it a unique place to study computer science.
Core Courses
Artificial Neural Networks and Deep Learning
Fall/Spring, 3 Credits
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.
Complex Networks
Fall/Spring, 3 Credits
According to the idea of ‘six degrees of separation,’ we all are only a few connections away from any other person on planet Earth. Although difficult to grasp, the small-world experiments and the study of networks have shown this idea to be true. Networks are present everywhere around us. They are embedded in our social relationships, the cells in our bodies, the World Wide Web, and the transportation media we use for local and international travel. This course will focus on computational and mathematical methods for characterizing, representing, and analyzing complex networks. We will explore various types of real networks, their properties, and their significance in science and society.
Game Development: Programming and Practice
Fall/Spring, 3 Credits
This course provides an overview of the phases of game development, with a focus on the pre-production and production stages. You will identify and discuss components within computer science that assist in game development, while having the opportunity to meet professional developers working in the field. In the corequisite lab course, you will learn about all the components that make up a game, and, as part of a semester-long project, work in groups to propose, develop, and create a game of your own. Through computer lab exercises, you will practice programming techniques while discussing the benefits and challenges of using different languages such as Python, C++, C#, and Java.
Core Course Study Tours
This program travels on Study Tours to the following destinations:
Artificial Neural Networks and Deep Learning:
- Week-Long Study Tour: Berlin or London or Madrid-Valencia or Stockholm
- Core Course Week: Denmark
Complex Networks:
- Week-Long Study Tour: Edinburgh
- Core Course Week: Denmark
Game Development: Programming and Practice + Lab:
Early in the semester, you delve into your academic focus during Core Course Week, in which you travel on a short Study Tour for three days in Denmark or a neighboring country, combined with a two-day seminar in Copenhagen. Later in the semester, you travel again with your Core Course on a week-long Study Tour in Europe.
While on tour, theories learned in the classroom come to life by meeting with professionals and experts in your field who contribute to furthering your understanding of course topics. Study Tours are hands-on and experiential, combining theory with practice, and expose you to additional cultural perspectives. You have the opportunity to visit sites and experts in your field of interest that you may not otherwise have access to.
Elective Courses
Add elective courses to complement your Core Course at DIS Copenhagen. You decide how to build your course load based on your needs and interests!
Electives range across disciplines and include research, workshops, studios, and even Exploration Electives, which come with a travel component.
Visit our website to view the full list of over 200 additional elective courses!
Prerequisites
Artificial Neural Networks and Deep Learning:
One year of computer science, a course in algorithms and data structures, one course in either probability theory, linear algebra, or statistics at university level. Knowledge of programming languages (e.g. in Python/Javascript/Java/C++/Matlab).
Complex Networks:
One year of computer science at university level. One of the computer science courses should be in algorithms and data structures. Knowledge of at least one programming language (e.g. Python/Javascript/Java/C++/Matlab). A course in probability is recommended.
Game Development: Programming and Practice:
One year of computer science and one mathematics course at university level. Knowledge of at least one programming language, preferably with object-oriented programming such as Java, C# or C++.
