Halmstad University

Halmstad University adds value, drives innovation and prepares people and society for the future. The University has from the start been characterised as forward-thinking and collaborative and offers popular and reality-based education programmes. The research is profiled within two focus areas: Health Innovation and Smart Cities and Communities. The School of Information Technology (ITE) is a strong research and education environment, with focus on smart technology and its applications. Students and researchers are working with everything from AI and information driven care to autonomous vehicles, social robotics and digital design.

Bayesian Statistics for Machine Learning

The course is broken down into: Basic Bayesian concepts Selecting priors, deriving some equations Bayesian inference, Parametric model estimation Sampling based methods Sequential inference (Kalman filters, particle filters) Approximate inference, variational inference Model selection (missing data) Bayesian deep neural networks

Critical Design and Practical Ethics for AI

The course is part of the programme MAISTR ( where participants can take the entire programme or individual courses. The course is for professionals and is held online in English. Application is open as long as there is a possibility of admission. The courses qualify for credits and are free of charge for participants who are citizens of any EU or EEA country, or Switzerland, or are permanent residents in Sweden. More information can be found at About the course Critical design and practical ethics for AI, 3 credits Who is this course for? Artificial Intelligence (AI) is being increasingly implemented and used in society today. It has already proven to have an impact on the individual, organization and society, and this impact will most likely only increase. Therefore, it is important to understand the ethical issues that may arise from use of AI, as well as to adopt a critical stance to the technology’s impact. The course introduces critical and ethical issues surrounding data and society, to train the student to problematize and reason about artificial intelligence (AI). You are most likely a designer, innovator, or product manager that works with digital services and products. What will you learn from this course? The course deals with different perspectives on AI and its real and potential effect on organizations and society. The course is based on five different perspectives on AI: accountability, surveillance capitalism, power and bias, sustainability, and trust. The course material consists of recent and relevant literature on the impact of, and critical perspectives on AI. Active discussions founded in different ethical perspectives are also an important part of the course. What is the format of this course? This course is primarily self-paced, with a few synchronous meetings. Most activities are based on the student’s having consumed specified material beforehand, such as video lectures, podcasts, articles, and books. Active discussions, both in online forums and during synchronous meetings, are an important part of the course.

Design for Extended Realities

The course consists of three parts that introduce and explore the design of extended realities along different axes: a framing perspective, illustrating what XR is, how it has evolved, and how designing XR differs from traditional digital design practices; a methodological perspective, detailing those XR-specific theory and methods that address XR design issues; and a practical perspective, exploring best practices and concrete design activities through direct application of these to a case. Each part consists of lectures, readings, supervision, and an assignment centered on the specific topics discussed in the part of the course.Assignments are carried out by students individually and will be peer-reviewed first and then discussed with the teachers and the class using a design critique approach.