Students attending this course will study some of the core algorithms and systems related to game development.

In this course, we teach both advanced machine learning (ML) approaches and hands-on skills for applying these approaches to data science problems.

This course provides an overview on the topics of bias and fairness in data, models, and algorithms, and on the associated ethical and accountability issues.

In this course, you will learn how to analyze and improve the performance of a computer system with a specific focus on data-intensive systems.

To investigate a system’s performance and come up with solutions to improve it, there are three key things to know.

1. How to devise a methodology to design experiments so that you can investigate the system’s performance,
2. The toolset to run the necessary experiments and collect the results, and
3. At least a basic understanding of the systems layers (hardware, operating systems, etc.) to be able to interpret your results and come up with solutions.

This is what we will cover in this course.

In this course, students learn how to work in data-driven design and development processes and what changes data analysis brings to the design and maintenance of games.

The course will introduce and cover basic concepts in Enterprise Architecture -an approach to understand, manage and develop business strategy in a complex IT landscape. There will be an introduction to the recognised frameworks and models in Enterprise Architecture.

This course aims to enable students to design and develop websites and interactive Web applications based on standard Web technologies and software frameworks.

The subject of the course is functional, declarative programming in general and F# in particular.

This course gives an introduction to IoT as well as practical experience with the design and implementation of end-to-end IoT systems.

Practical examples and exercises will predominatly be from domains Energy and Environment.

The students will learn theoretical foundations of IT-enabled process improvement and apply these to a real life practical context by working with an organisation.

The objective of the course is to introduce students to important philosophical and historical perspectives on science and technology, as well as to more general epistemological and reflexive issues related to business informatics as a social science discipline. Throughout the course, the student will become acquainted with a series of concepts within a selection of thematic fields that can be used to critically interrogate empirical phenomena relating to ‘science’ and ‘technology’. 

The main outcome of the course is that students are equipped with an understanding of core theories, concepts and methods in co-design and participatory design approaches, and their historical grounding and development. Students will also have experience from applying co-design methods in a live project with real stakeholders, and reflecting on the process and results.

The course runs for the last time in the current format in Spring 2025

The course will be offered in English in Spring  2025 and a slight revision of course is expected.

Kursets mål er, at de studerende har (1) en grundlæggende forståelse af begreberne data, netværk og dataanalyse; og (2) en værktøjskasse med teknikker og teorier til at diskutere ideen om netværk og data som grundlag for konceptualisering af et netværkssamfund.

The course is offered for the last time in the current format in Spring  2025 ref. the revision of the BDDIT programme

This course gives a fundamental overview of Android programming concepts and the best practices for mobile app development.

The course "DevOps, Software Evolution and Software Maintenance" is a BSc elective.

In this course, the students will discover all the software engineering activities that take place after an initial software product is delivered or after a legacy system is taken over from a theoretical and practical perspective. Students (in groups) will take over such a system that is live and serving users, they will refactor and migrate it to the languages and technologies of their liking. All subsequent DevOps, software evolution and software maintenance activities will be performed directly on the systems of the students.

The course "DevOps, Software Evolution and Software Maintenance" is an MSc elective.

In this course, the students will discover all the software engineering activities that take place after an initial software product is delivered or after a legacy system is taken over from a theoretical and practical perspective. Students (in groups) will take over such a system that is live and serving users, they will refactor and migrate it to the languages and technologies of their liking. All subsequent DevOps, software evolution and software maintenance activities will be performed directly on the systems of the students.

The course aims to train the students in conducting a thorough and valid analysis of online data sources with the use of basic programming, statistics and business intelligence tools. 

This course is designed to give students a basic introduction to programming and data processing. Students will get a hands-on introduction to the Python programming language and how to work with tabular data. This will enable them to solve simple programmatic tasks as well as to get an idea of what the role of the programmer entails. After the course student will be able to discuss and reflect on challenges and opportunities derived from approaching the world through algorithms.

The purpose of this course is to explore play as an expressive form and creative framework outside of the domain of games. As such, the learning goals and activities are not oriented towards game design. This course will focus on drawing into the digital design domain inspiration and practices from play and computer games.

This course is designed to expand the intellectual and professional scope of interaction design students.

In collaboration with industrial partners, students will apply Scrum in practice and reason about its application in a controlled yet realistic environment.

Algorithmic problem solving is the art of designing algorithms to solve challenging programming problems. This requires extensive practice in classifying problems, choosing the right data structures, and identifying suitable algorithms. This is very different to a standard algorithm and data structure course, where the focus is on understanding the tools at hand, but not on using them to solve problems. This course bridges the gap between theoretical knowledge and practical solutions to computational problems.

Algorithmic problem solving is the art of designing algorithms to solve challenging programming problems. This requires extensive practice in classifying problems, choosing the right data structures, and identifying suitable algorithms. This is very different to a standard algorithm and data structure course, where the focus is on understanding the tools at hand, but not on using them to solve problems. This course bridges the gap between theoretical knowledge and practical solutions to computational problems.

Through this course, the students will learn about the aspects of game programming commonly involving artificial intelligence methods, which methods are used and how to implement them.

The course provides a basic introduction to scientific thought and introduces central philosophical perspectives on science, epistemology and technology, including central concepts in scientific methodology. The course puts a special focus on IT technologies, exploring its foundations and ethical implications.  

This course provides an introduction to the fundamental concepts of cryptography, the practice of protecting information and securing communication in computer systems. We start with classical encryption techniques, and consider modern private-key and public-key crypto systems and study their security against eavesdroppers or attackers, who tamper with network traffic. The course is aimed at students with a background in computer science or mathematics, and will include both theoretical and programming exercises. 

The course gives an in-depth introduction to the fundamental principles of statistics.

This course offers a comprehensive exploration of service design and management, equipping students with essential processes, principles, methods, and tools. It focuses on the strategic design and management of services, including digital components, and draws on expertise from various disciplines within service design and management. Through lectures, in-depth case studies, and interactive hands-on exercises, students will examine the characteristics and dynamics of services and service ecosystems. The course aims to deepen students' understanding of how services can be effectively designed, managed, and implemented to deliver substantial value to users, providers, and other stakeholders.

This course examines organizations in light of contemporary challenges with digitalization. It explores organizational perspectives on digitalization and cover theories that can help us better understand, and critically reflect upon, such profound challenges, while also offering hands-on approaches to managing them. Furthermore, it investigates questions of the changing nature of work, and themes such as leadership, management, and organizing in order to make students both knowledgeable about, and skilled in the practice of, and engaging with, digital transformation.

This course provides an introduction to Information Security Risk Management. The course enables students to lead risk assessments, and reflect on the applicability of different techniques for risk assessment and management.

This course provides an introduction to Information Security Risk Management. The course enables students to lead risk assessments, and reflect on the applicability of different techniques for risk assessment and management.

This course introduces theories and methods of innovation with a particular emphasis on products, services and systems that relate to or involve digital technologies. The course involves in-depth knowledge of innovation types, organizational context, identification of innovation opportunities, strategy and competitive analysis. Through a case-driven engagement with external companies and organizations, the students will develop, evaluate, present and argue for concrete concepts.

This course is a new course for the KDDIT 2024 intake. KDDIT students enrolled before 2024 and who has not yet taken Design-driven Innovation course, should sign up for KADDINN1KU Designdrevet innovation (see also transitional provisions)  

In this course, students will learn about qualitative research methods and the constitutive elements of qualitative research designs.  

The “Database & Information Systems Foundations” course provides a comprehensive introduction to the key concepts and components of modern information systems, including hardware, software, users, and organizations. Students will explore the architecture of database systems, design Entity-Relationship (ER) and relational models, and develop SQL queries for real-world use cases. Additionally, the course covers business process modeling and guides students through the design and implementation of database-driven programs, equipping them with essential skills for building and managing information systems.

Learn to make custom data visualisations by designing with data. Uncover the possibilities of data visualization and discover how to play with data in code.

The goal of this course is to equip students to understand how underlying technological and social infrastructures shape the digital economy.

This course introduces basics of Bayesian statistics, Bayesian data analysis, Bayesian learning, and the programming tools that enable automation of these methods. The course emphasizes programmable statistical methods over pen and pencil analytics.