DATA ANALYTICS IN VIRTUAL PRODUCTION

In this course you will learn state-of-the-art statistical modelling for the purpose of analysing industrial data. The course also presents the basics of relational databases and data manipulation techniques needed to prepare the data for analysis.

The course is part of the programme MAISTR (hh.se/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 antagning.se. About the course Smart Healthcare with Applications, 4 credits Who is this course for?The course suits you with any Bachelor’s degree (equivalent of 180 Swedish credit points / ECTS credits at an accredited university) who have an interest in applying Artificial Intelligence (specifically Machine Learning) to healthcare. Leadership/management experience in health-related organization/industry OR a Bachelor degree in computer science is advantageous. What will you learn from this course?Healthcare as a sector together with other health-related sources of data (municipalities, home sensors, etc.), is now in a place and can take advantage of what data science, Artificial Intelligence (AI), and machine learning (ML) have to offer. Information-driven care has the potential to build smart solutions based on the collected health data in order to achieve a holistic fact-based picture of healthcare, from an individual to system perspective. This course aims to provide a general introduction to information-driven care, challenges, applications, and opportunities. Students will get introduced to artificial intelligence and machine learning in specific, as well as some use cases of information-driven care, and gain practice on how a real-world evidence project within information-driven care is investigated. What is the format for this course?Instruction type: The lectures, announcements, and assignments of this course will be fully online via a learning management system and presented in English. Each lecture is delivered through a video conference tool with a set of presentation slides displayed online during each class session. Online practical labs (pre-written Python notebooks) are also provided in the lectures.

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

The aim of this course is that students will learn about the analysis, design, and programming of deep learning algorithms. The course is part of the programme MAISTR (hh.se/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 antagning.se. About the course Applied Deep Learning with PyTorch, 5 credits Who is this course for?This course provides the theoretical and practical aspects of deep neural networks. It is intended for students with a background in computer science and engineering. What will you learn from this course?Students will learn about the analysis, design, and programming of deep learning algorithms. The course has two modules: theory and practice. The theoretical content covers basic principles of multi-layer perceptions, spatio-temporal feature extraction with convolutional neural networks (CNNs), and recurrent neural networks (RNNs), classification and regression of big data, and generating novel data samples using generative models. The practical sessions cover the basics of programming with PyTorch. For instance, image classification and semantic segmentation using CNNs, future image frame prediction with RNNs, and image generation with generative adversarial networks. What is the format for this course?Instruction type: Teaching is in English and fully online. It consists of lectures, computer exercises, and project work. In the computer exercises, the student solves small problems using deep learning models. After programming various exercises, the participants will develop an advanced deep learning project. Participants will be encouraged to bring their own data. High-end GPU machines can be provided for the exercises and project.

The course is part of the programme MAISTR (hh.se/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 antagning.se. 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.

I den här kursen får du en ökad förståelse för vad digitalisering och digital transformation innebär. Du lär dig mer om varför digitalisering kan vara ett bra sätt att utveckla en verksamhet samt hur du kan arbeta systematiskt med den förändringsprocess som digitalisering innebär. Detta kan hjälpa dig att förbättra effektiviteten och innovationsförmågan i din organisation samt bidrar till att utveckla din kompetens. Vad innebär digitalisering och digital transformation och hur kan företag och organisationer arbeta med digitalisering? Det är frågor som du kommer lära dig mer om här. Kursens tar utgångspunkt i digitalisering som tillämpning av digital teknik i företag och organisationer och behandlar samspelet mellan tillämpning av digital teknik och organisationsförändring. Kursen består av följande moduler: Introduction to digitalisation and digital transformation sätter fokus på digitalisering och digital transformation och hur digitalisering kan användas för effektivisering och innovation. Business development through digitalisation introducerar olika modeller för digitalisering och digital transformation där deltagarna ges möjlighet att praktisera några av dessa i sin verksamhet, till exempel modeller för kartläggning av digital mognad och verksamhets- och förändringsanalys. Data driven organizations and data use berör data som resurs vid utvecklingsarbete, till exempel verksamhets-, produkt-, tjänsteutveckling). Deltagarna introduceras i hur data kan utgöra resurs för olika användningsområden, i olika kontext och vilka nyttor och värden som kan förväntas och realiseras med hjälp av data. Leadership and organization in the age of digital transformation fokuserar på ledning och organisering av digital transformation och hur agila arbetssätt, perspektiv och värderingar kan stötta den pågående förändringsprocess som digitalisering medför.  Diskussionsinnehållet i kursen tas delvis fram av och samskapas av deltagarna själva genom att de tillämpar teorier, begrepp och modeller på egna erfarenheter. Kursen förutsätter självständigt arbete, kontinuerlig textinläsning samt aktivt och reflekterande deltagande i undervisningen. Kursen vänder sig till dig som är yrkesverksam och som vill utveckla din kompetens inom digitalisering och digital transformation, förändringsledning och hur digitalisering kan användas för effektivisering och innovation i företag och organisationer. Den passar exempelvis dig som är chef, projekt- eller processledare eller som arbetar med affärs- och verksamhetsutveckling samt IT-frågor.  Kursen är på avancerad nivå och ger 5 högskolepoäng. Den riktar sig till dig som är yrkesverksam och ges på deltid så att studier och arbete kan kombineras. Undervisningen sker på svenska och engelska och genomförs på distans via Canvas som är Karlstads universitets lärplattform. Kursen är kostnadsfri. Antal platser är begränsat. Läs mer och anmäl ditt intresse till nästa kursomgång hösten 2024: https://www.kau.se/ctf/ise/digitalisering-och-digital-transformation