Enkeltfag på bachelorniveau

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 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. 

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.

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.  

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

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.

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.

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.