COURSE DESCRIPTION
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.
Today, the explosion of data has created new opportunities to apply machine learning (ML). Handling of the large amounts of data created by the very rapid digitization would not be possible without Machine Learning (ML). The purpose of the course "Introduction to Machine Learning" is to give you the foundation for ML. You will get an introduction to the basic areas of ML: data, statistics and probability for ML.
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.
How can we live a good life on one planet with over seven billion people? This course will explore greening the economy on four levels – individual, business, city, and nation. We will look at the relationships between these levels and give many practical examples of the complexities and solutions across the levels. Scandinavia, a pioneering place advancing sustainability and combating climate change, is a unique starting point for learning about greening the economy. We will learn from many initiatives attempted in Scandinavia since the 1970s, which are all potentially helpful and useful for other countries and contexts. The International Institute for Industrial Environmental Economics (IIIEE) at Lund University is an international centre of excellence on strategies for sustainable solutions. The IIIEE is ideally suited to understand and explain the interdisciplinary issues in green economies utilising the diverse disciplinary backgrounds of its international staff. The IIIEE has been researching and teaching on sustainability and greener economies since the 1990s and it has extensive international networks connecting with a variety of organizations.
Business models that efficiently contribute to reduction of material use and waste are key to successful transition towards sustainability. This course has a particular focus on the interplay between business models, product innovation and production processes. Through this course, you will explore the critical relationship between sustainable practices and business strategies, preparing you to contribute meaningfully to the circular economy and sustainable development initiatives In this course, you will be introduced to systematic working methods for business development in practical contexts, with a specific focus on innovation and creativity. The goal of the course is to provide a deep understanding of the application of various business model practices in different types of development work. The objective is for course participants to enhance their ability to understand and apply business development processes in the manufacturing industry and gain deeper insights into how these processes relate to organizations' innovation and business strategies in order to achieve circular flows, resilience, and sustainability. The teaching consists of self-study using course literature, films, and other materials through an internet-based course platform, as well as scheduled webinars and written reflections. There are no physical meetings; only digital online seminars are included. Study hours 40 hours distributed from week 3, 2025 to week 8, 2025. Webinar 1: January 13thWebinar 2: January 20thWebinar 3: February 3rdWebinar 4: February 17th Target GroupThis course is primarily intended for engineers in management or middle management positions within industry, whether they are recent graduates or individuals with extensive experience. The course is suitable for individuals with backgrounds in mechanical engineering, industrial engineering management, or similar educational background. Entry RequirementsTo be eligible for this course, participants must have completed courses equivalent to at least 120 credits, with a minimum of 90 entry Requirement credits in a technical subject area, with at least a passing grade, or equivalent knowledge. Proficiency in English is also required, equivalent to English Level 6. Educational package in circular economyThe course Product/production and business development for circular flows is an introduction of the educational package starting again spring 2024 and will also run spring 2026. This course: Business development for circular flow together with Product development for circular flows (starting March 3) and Production for cirkular flows (starting April 28) are free standing independent courses that build on knowledge in the field.