COURSE DESCRIPTION
Kursen syftar till att ge en introduktion till praktisk AI, med fokus på grundläggande maskininlärning. Syftet är att förstå hur man kan skapa AI-system med hjälp av maskininlärning, få inblick i teknikens möjligheter och begränsningar, samt få en överblick över vanliga metoder för maskininlärning.
Du kan börja läsa kursen i stort sett när du vill då kursen är en online-kurs med flexibel antagning. Du gör ansökan till den termin du tänker börja läsa kursen. Vill du börja direkt så ansöker du till innevarande termin. Termin väljer du här ovan, så kommer du till rätt ansökningstillfälle.
Kursen är en distanskurs som görs i egen takt och hanteras i sin helhet i en web-baserad kursmiljö. Kursen baseras på självstudier av kursmaterialet och examineras med självrättande tester och inlämningar. Du som har gjort Elements of AI, Part 2: Building AI kan anmäla dig till den här kursen för att få dina resultat validerade. Detta innefattar att göra ett valideringstest med frågor motsvarande de som finns i Elements of AI, Part 2: Building AI för att säkerställa att det verkligen är du som gått igenom kursen. För mer information se denna länk.
Kursen handleds över internet.
Observera att du vid ansökan till kursen måste kunna styrka att du har grundläggande behörighet. Om dina gymnasiemeriter inte redan finns på dina sidor på antagning.se så behöver du ladda upp gymnasieexamen, eller motsvarande, på antagning.se i samband med din ansökan.
Denna kurs kan du också läsa via vår samarbetspartner Nitus lokala lärcentra, som finns på ett flertal platser i Sverige. Läs mer via denna länk.
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 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.
This course has an English version. Look for course with title "Why choose wood for the next high rise building?" KursbeskrivningOlika typer av biomaterial (t.ex. trä) är mycket viktiga i utmaningen att avkarbonisera byggmiljön och minska koldioxidavtrycket för byggnader och infrastruktur genom att ersätta material som stål och cement som har höga koldioxidutsläpp. Samtidigt får vi inte glömma bort att biologisk mångfald, natur och sociala värden i våra skogar är viktigt att behålla samtidigt som skogsbruk bedrivs. I kursens 13 moduler tas skogsbrukets kretslopp upp inklusive avverkningsmetoder, biologisk mångfald, skogsskötsel, logistik, skogens roll i klimatomställningen, kolinlagring, miljöfördelar med att bygga flervåningshus i trä mm. Syftet är att ni som deltar i kursen ska få en gemensam förståelse av det svenska skogsbruket för att ni sen ska kunna fatta välgrundade beslut om materialval vid nästa byggprojekt. KursperiodKursen kommer att vara aktiv under 3 år. InnehållSkogshistoria: Skogens nyttjande i Sverige genom historienSkogsbruksmetoder och skogsskötselSkogsföryngringVirkets egenskaperMätning av skog och virkeSkogsträdsförädling: nutid och framtidSkogens kolbalans och klimatetAffärsmodeller och marknadsutveckling: Fokus flervåningshus med trästommarNaturvård och biologisk mångfald i skogen Kursens uppläggKursen är helt digital med förinspelade föreläsningar. Du kan delta i kursen i din egen takt. Modulerna avslutas med quiz där du kan testa hur mycket du har lärt dig. Du kommer få kunskap omEfter avslutad kurs kommer du att ha lärt dig mer om olika skogliga begrepp, förvärvat kunskap om skogens nyttjande i Sverige genom historien, ökat dina kunskaper om skogsskötsel och hur olika skogsskötselmetoder påverkar den biologiska mångfalden i skogen, lärt dig om skogsbrukets kretslopp – från föryngring till slutavverkning mm. Vem vänder sig kursen till?Den här kursen är tänkt för dig som är yrkesverksam arkiktekt, anställd på kommun som arbetar med stadsplanering och byggande, verksam i bygg- och anläggningsbranschen samt verksam i andra relaterade yrken. Detta är en introduktionskurs och kommer att bidra till en kompetenshöjning i hela byggsektorns ekosystem vilket ökar branschens internationella konkurrenskraft, samtidigt som det ger viktiga förutsättningar för utvecklingen av framtidens hållbara, vackra och inkluderande städer. Eftersom kursen är öppen för alla hoppas vi att fler grupper, exempelvis studenter, doktorander, skogsägare och andra med skogsintresse tar kursen, tar del av inspirerande föreläsningar där vetenskaplig kunskap som producerats huvudsakligen inom SLU presenteras.För mer information kontakta kurskoordinator dimitris.athanassiadis@slu.se
Virtual commissioning (VC) is a technique used in the field of automation and control engineering to simulate and test a system's control software and hardware in a virtual environment before it is physically implemented. The aim is to identify and correct any issues or errors in the system before deployment, reducing the risk of downtime, safety hazards, and costly rework. The virtual commissioning process typically involves creating a digital twin of the system being developed, which is a virtual representation of the system that mirrors its physical behaviour. The digital twin includes all the necessary models of the system's components, such as sensors, actuators, controllers, and interfaces, as well as the control software that will be running on the real system. Once the digital twin is created, it can be tested and optimized in a virtual environment to ensure that it behaves correctly under various conditions. The benefits of using VC include reduced project costs, shortened development time, improved system quality and reliability, and increased safety for both operators and equipment. By detecting and resolving potential issues in the virtual environment, engineers can avoid costly and time-consuming physical testing and debugging, which can significantly reduce project costs and time to market. The course includes different modules, each with its own specific role in the process. Together, the modules create a comprehensive virtual commissioning process that makes it possible to test and validate control systems and production processes in a simulated environment before implementing them in the real world. Modeling and simulation: This module involves creating a virtual model of the system using simulation software. The model includes all the equipment, control systems, and processes involved in the production process. Control system integration: This module involves integrating the digital twin with the control system, allowing engineers to test and validate the system's performance. Virtual sensors and actuators: This module involves creating virtual sensors and actuators that mimic the behavior of the physical equipment. This allows engineers to test the control system's response to different scenarios and optimize its performance. Scenario testing: This module involves simulating different scenarios, such as equipment failures, power outages, or changes in production requirements, to test the system's response. Data analysis and optimization: This module involves analyzing data from the virtual commissioning process to identify any issues or inefficiencies in the system. Engineers can then optimize the system's performance and ensure that it is safe and reliable. Expected outcomes Describe the use of digital twins for virtual commissioning process. Develop a simulation model of a production system using a systems perspective and make a plan for data collection and analysis. Plan different scenarios for the improvement of a production process. Analyze data from the virtual commissioning process to identify any issues or inefficiencies in the system and then optimize the system's performance. Needs in the industry Example battery production: Battery behaviors are changing over time. To innovate at speed and scale, testing and improving real-world battery phenomena throughout its lifecycle is necessary. Virtual commissioning / modeling-based approaches like digital twin can provide us with accurate real-life battery behaviors and properties, improving energy density, charging speed, lifetime performance and battery safety. Faster innovation (NPI) Lower physical prototypes Shorter manufacturing cycle time Rapid testing of new battery chemistry and materials to reduce physical experiments Thermal performance and safety It’s not just about modelling and simulating the product, but also validating processes from start to finish in a single environment for digital continuity. Suggested target groups Industry personnel Early career engineers involved in commissioning and simulation projects Design engineers (to simulate their designs at an early stage in a virtual environment to reduce errors) New product introduction engineers Data engineers Production engineers Process engineers (mediators between design and commissioning) Simulation engineers Controls engineer System Integration
The EU’s circular economy strategy increases the need for expertise in the use of sustainable and recycled materials. This course provides tools and knowledge for the use of sustainable materials, development towards sustainability of existing materials, recycled and upcycled materials and how they contribute to the green transition through reduced energy consumption, longer lifespan, reduced costs, reduced waste volumes, better user-friendliness and opportunities for social entrepreneurship. The course will give you the opportunity to work on your own project in your own context and include different creative and practical tools. Course content Part 1: Introduction to the Circular Economy Part 2: Design for Recycling Part 3: Use of Recycled Materials Part 4: Substitution with Sustainable Alternatives Part 5: Conditions for Circular Systems and Economies Course design Open online course with pre-recorded lectures, interview and workshops, with reading, reflection and creative assignments. Self-paced, start and finish when you want to. This course takes about 80 hours to complete. You will learn How circular economy, material flows and sustainable materials can be understood in a broader sustainability context. Using various tools and models to analyze and improve material flows and product design. Practically apply and implement the knowledge in the course to their own business or a chosen project. Who is the course for? The course is aimed at professionals in industry, waste management, construction, material production, product development, recycling solutions, local and regional government, design and different creative professions. It is also open to students on all levels and participants without an academic background who want to deepen their knowledge in circular economy and sustainable material choices.