Applied Computer Science

Students will gain knowledge of models, theories, and frameworks for information systems development from the research traditions of Action Research, Design Science, Scandinavian Participatory Design, and Engaged Scholarship. Students will obtain an overview of the technologies, tools, and platforms central to the upcoming courses Master programme. Students will also gain knowledge of software documentation, data collection, data analysis, and technical writing.

Central topics includes applied computer science.

Students will gain advanced knowledge of key theories and concepts of big data and machine learning. They will acquire specialised problem-solving skills, being able to bring together several key technologies used in manipulating, storing, and analysing big data. They shall take responsibility to conduct the planning and implementation of activities and evaluate the organisations value of big data.

Students will learn how to extract and identify useful features that best represent the data, learn about the most important machine learning algorithms as well as evaluating the performance of the chosen machine learning algorithm.

This course provides an introduction to interaction oriented software architectures, to provide the students with analytical skills, development methodologies and technological skills that are necessary to analyze, plan and implement architectures for integration projects. The course will be taught in the context of enterprise systems and distributed systems, which means that issues of network protocols, scalability and security will be emphasized.

The central topics of this course include applied computer science and systems development.

The main aim of this course is to provide students with the fundamental knowledge of ethics and sustainability necessary for responsible innovation and the development of new information technologies (IT) in the modern society. The central topics include the role of ethics in responsible innovation and IT development; information privacy concerns, social, economic, and environmental impacts of innovations and new ITs; and how IT development and innovation can contribute to achieving the UN Sustainable Development Goals. In covering ethical and sustainability issues, the course addresses the perspectives of various stakeholders at the individual level (IT developers, innovators, consumers, investors), the organizational level (commercial, public, and non-governmental organizations), and the societal level (local and regional communities, nations, international society). Group work on possible solutions to real-life ethical and sustainability challenges constitutes an essential part of the course.

Students will gain knowledge about theoretical principles and computational techniques for visual analytics. The course will enable students to design, demonstrate and evaluate information dashboards for organizations. The students will be able to reflect on the different models, theories, and frameworks for technology integration from a visual analytics perspective.

Central topics include applied computer science.

Students will gain in depth knowledge of mobile computing and introduce the Internet of Things (IoT). Students will further acquire knowledge of theories/models of mobile and pervasive computing applications, technologies and common research paradigms in mobile and pervasive computing such as context awareness, computing in an environment with limited resources, sensor-based interaction, and smart-device management. They will acquire skills in application design, architecture and implementation. Students will be expected to be able to analyse, discuss and critically reflect upon theories and research issues in mobile computing and internet of things.