COURSE DESCRIPTION
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 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
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.
WHat you will learn Increased knowledge on sustainable cities and communities. Deeper understanding of the relationship between urbanization, decarbonisation and sustainability. Improved critical thinking on the opportunities and challenges for sustainable cities and communities as engines for greening the economy. Expanded ability to use systems thinking to assess sustainable cities and communities. About this SpecializationIn this specialization you will learn how to drive change in cities and communities towards sustainable, climate friendly, just, healthy and prosperous futures, and you will boost your career with new knowledge, understanding and skills for navigating urban transformations. This specialisation brings together a series of cutting-edge courses with world-leading teachers on cities, communities, sustainability, governance and innovation. This specialization is offered by the IIIEE at Lund University and the City Futures Academy – an online learning community on urban transformations. Our flagship course, Greening the Economy: Sustainable Cities, is ranked in the Best Online Courses of All Time by Class Central. The ranking by Class Central contains 250 courses from 100 universities based on 170,000 reviews. Our specialisation builds on the success of the Greening the Economy: Sustainable Cities course. A key approach embedded in the courses in this specialisation is the role of experimentation in urban transformations. In particular, urban living labs are highlighted as a means for catalysing change in cities and communities towards sustainable, climate friendly, just, healthy and prosperous futures. The experimentation within urban living labs offers the potential for accelerating transformations and systematic learning across urban and national contexts. Applied Learning Project Learners are introduced to key facts and insights about sustainable cities and communities as engines for greening the economy, then tasked with developing this understanding through readings and practice exercises that highlight the role of urban living labs in creating sustainable cities and communities. Specifically, you will learn: how to work with greening the economy through cities and communities; how to design and implement urban living labs for accelerating change in cities and communities; how to build resilience and create a host of benefits from nature-based solutions in cities and communities; and how to influence consumption patterns in cities and communities through sharing practices . Further documentaries and quizzes will provide you with critical thinking and a broader and deeper perspective that are essential to understanding and creating sustainable cities and communities.
Gain essential practical skills in the application of robotics to understand how to use robotic tools across various industries. On this two-week course you’ll develop a working knowledge of the use of robotics, gaining essential practical skills for robotic applications. Delving into the fundamentals of robotics, you’ll be equipped with the basics of 3D modelling, object detection, computer vision, and image processing. You’ll discover examples and get hands-on experience in developing engaging and useful robotics applications. The skills you gain in this course will help you understand how to develop robotic tools in application across various sectors. Delve into object detection Gain practical skills in the application of robotics Learn from the experts at Luleå University of Technology This course is designed for anyone interested in learning how to develop robotic tools. It will be most beneficial for those who have some theoretical knowledge of robotics and want to gain more hands-on experience. This course will be given in English.
Hydrogen will play a major role in the transition to a low-carbon society. Still, it also introduces demanding conditions for materials and components across the entire value chain, from production and compression to storage, transport, and end-use. Many of the most critical technical risks in hydrogen systems are materials-related, including loss of ductility and premature fracture, accelerated fatigue, unexpected leakage, seal degradation, corrosion, and performance degradation over time. Understanding these mechanisms is essential for making safe, reliable, and cost-effective engineering decisions. This course offers a practical, engineering-focused introduction to materials in the hydrogen economy, including catalysts in hydrogen production and materials used in hydrogen storage and transportation, as well as their impact on component lifetime and system safety. You will learn how hydrogen enters materials, how it moves (diffusion and permeation), where it accumulates (trapping sites), and how these processes can trigger degradation. A special focus is placed on hydrogen embrittlement in metals, particularly in steels and welded joints, because these materials are widely used in pipelines, pressure vessels, fittings, and structural components. The course also covers non-metallic materials that are crucial for hydrogen infrastructure, including polymers, elastomers, and coatings used in liners, seals, hoses, gaskets, and protective layers. In addition to the fundamental mechanisms, the course connects theory to real engineering choices. You will discuss which materials are suitable under different hydrogen conditions (pressure, temperature, purity, moisture, cycling), what typical failure modes look like, and what mitigation strategies can be used in practice, such as material selection, heat treatment, surface engineering/coatings, design measures, operating-window choices, and inspection/testing approaches. The course also introduces materials challenges in key hydrogen technologies such as electrolysers and storage solutions, highlighting how degradation and compatibility issues influence performance and maintenance needs. You will also discuss hydrogen carriers and their storage and utilization solutions. The teaching format combines short, focused lectures with seminar discussions and an applied assignment. Participants are encouraged to bring examples from their own work or studies (for example, a pipeline material choice, a valve and seal problem, a storage tank concept, or an electrolyser component, chemical and physical storage systems) and use these as case studies during seminars and in the final assignment. By the end of the course, you will have both the conceptual framework and the practical tools needed to evaluate materials risks in hydrogen applications and make better-informed decisions for real systems. What you will be able to do after the course After completing the course, you will be able to: Explain key mechanisms of hydrogen–materials interactions and their consequencesIdentify materials-related risks in hydrogen production, storage, and transportationEvaluate and justify materials choices for hydrogen components and systemsPropose mitigation strategies (design choices, coatings, operating conditions, testing/inspection approaches) Course structure (March 2–31) 6 lectures: Overview of hydrogen economy and materials, Materials in hydrogen production, Hydrogen materials interaction-core concepts, mechanisms, and engineering implications, Hydrogen Carriers, and materials selection and design2 seminars: discussion of case studies and participant problems/components1 assignment: applied analysis/report linked to a realistic hydrogen application (can be connected to your work/project) March 2 Lecture-Introduction 10:00-10:45 Farid Akhtar Introduction March 5 Lecture I 09:30-11:00 Valentina Zaccaria hydrogen production and utilization – An overview March 6 Lecture II 10:00-11:30 Farid Akhtar Materials in Hydrogen Infrastrucutre- An Overview March 12 Lecture III 10:00-12:30 Alberto Vomiero/Marshet Sendeku Materials in Hydrogen production and conversion March 17 Lecture IV 10:00-11:30 Farid Akhtar Hydrogen Embrittlement Mechanism and Theory March 19 Seminar I 10:00-12:00 Farid Akhtar Topic I March 23 Lecture V 10:00-11:30 Farid Akhtar Mitigating Hydrogen embrittlement: Materials selection and development March 26 Seminar II 10:00-12:00 Farid Akhtar Topic II March 30 Discussion/White Board 09:30-11:00 Farid Akhtar Sorting Challenges For whom Engineers and professionals working with hydrogen technologies (or planning hydrogen projects)Master’s students in relevant fields Entry requirements Recommended background in engineering/natural sciences (materials/mechanics/chemistry/physics or equivalent). Relevant professional experience can also qualify. Examination Based on: Assignment (report and/or presentation)Participation in lectures, seminars and discussions Course responsible/examiner: Farid Akhtar