Applications 2025-09-15 - 2025-10-15
COURSE DESCRIPTION
In the era of shift towards green transition, industries face unique challenges and generates numerous opportunities. This course, "Intelligent Asset Management and Industrial AI" is designed to equip professionals with the knowledge and tools necessary to support advanced technologies in achieving environmental sustainability.
Industries play a major role in contributing to the global economy that is accompanied with a significant share towards environmental degradation. The growing climatic concerns and degradation of natural resources has urged the need to reduce carbon footprints, minimize waste, and optimize resource utilization such that a green transition is achieved. Intelligent Asset Management and Industrial AI are at the forefront of this transformation offering innovative solutions to enhance operational efficiency, reduce environmental impact and support the industry’s commitment to sustainability. Furthermore, the course can help a professional to optimize the usage of resources, look for energy efficient systems, consider environmental changes, develop sustainable solutions, and integrate advanced technologies towards green transition.
This is a problem-based course specific to an industrial sector. The problems can be provided by the course supervisor, or the participants can bring their own problems from their work. Common problems include e.g. asset management by balancing cost against performance, identifying, detecting, predicting, and planning for unexpected outages, disruptions or failures, exploring challenges and opportunities with AI and digitisation, monitoring the condition of industrial assets, and achieving sustainability goals.
Course Start
The course starts in the spring of 2026, more information will follow.
Applications are made via www.antagning.se between 2025-09-15 and 2025-10-15.
Target group
The target group includes individuals working in various industries such as railway, mining, transportation, construction, manufacturing, logistics, energy, and other organizations that are or planning to implement asset management systems. This course can be suitable for professionals ranging from asset managers, maintenance and reliability professionals, operation managers, engineers, project managers, and asset management consultants.
Online seminars
Five onlineseminars, dates will be presented later.
Entry requirements
Bachelor’s degree of at least 180 ECTS or equivalent, which includes courses of at least 60 ECTS in for example one of the following areas: Maintenance Engineering, Mechanical Engineering, Materials Science, Data Science, Computer Engineering, Civil Engineering, Electrical and Electronics Engineering or equivalent.
Or professional experience requirements four to five years of experience in relevant industries.
This course teaches you how to build convolutional neural networks (CNN). You will learn how to design intelligent systems using deep learning for classification, annotation, and object recognition. It includes three modules: Image processing: Introduction of industrial imaging through big data and fundamentals of image processing techniques Deep learning with convolutional neural network: Overview of neural network as classifiers, introduction of convolutional neural network and Deep learning architecture. Deep learning tools: Implementation of Deep learning for Image classification and object recognition, e.g. using Keras.
The rapid development of digital technologies and advances in communications have led to gigantic amounts of data with complex structures called ‘Big data’ being produced every day at exponential growth. The aim of this course is to give the student insights in fundamental concepts of machine learning with big data as well as recent research trends in the domain. The student will learn about problems and industrial challenges through domain-based case studies. Furthermore, the student will learn to use tools to develop systems using machine-learning algorithms in big data.
The course aims to give insights in fundamental concepts of machine learning for predictive analytics to provide actionable, i.e., better and more informed decisions in, forecasting. It covers the key concepts to extract useful information and knowledge from data sets to construct predictive modeling. The course includes three modules: Introduction: overview of Predictive data analytics and Machine learning for predictive analytics. Data exploration and visualization: presents case studies from industrial application domains and discusses key technical issues related to how we can gain insights enabling to see trends and patterns in industrial data. Predictive modeling: consists of issues in construction of predictive modeling, i.e., model data and determine Machine learning algorithms for predicative analytics and techniques for model evaluation.
Opens in May 2025. The Swedish version of the course, namely ”Varför välja trä vid nästa byggprojekt?” is already open. For more iformation contact course coordinator dimitris.athanassiadis@slu.seCourse DescriptionDifferent types of biomaterials (e.g., wood) are crucial in the challenge of decarbonizing the built environment and reducing the carbon footprint of buildings and infrastructure by replacing materials like steel and cement, which have high carbon dioxide emissions. At the same time, we must not forget that it is important to preserve biodiversity and the social values of our forests. The 13 modules of the course cover many forestry related subjects, including harvesting methods, biodiversity, forest management, logistics, the role of forests in the climate transition, carbon storage, environmental benefits of multi-story buildings with wood, and more. The goal is that participants will gain a shared understanding of Swedish forestry so that they can make well-informed decisions about material choices for their next construction project. Course PeriodThe course will be active for 3 years. Content Forest history: The utilization of forests in Sweden throughout the past years Forestry methods and forest management Forest regeneration Wood properties Forest mensuration Forest tree breeding The forest's carbon balance Business models and market development: Focus on wood high rises Nature conservation and biodiversity in the forest Course StructureThe course is fully digital with pre-recorded lectures. You can participate in the course at your own pace. Modules conclude with quizzes where you can test how much you have learned. You will learn aboutUpon completion of the course, you will have learned more about various forest-related concepts, acquired knowledge of forest utilization in Sweden throughout the past years, increased your understanding of forest management and how different management methods affect biodiversity in the forest, and learned about the forestry cycle—from regeneration to final harvesting, etc. Who is this course for?This course is designed for professionals such as architects, municipal employees working with urban planning and construction, individuals in the construction and civil engineering sector, and those in other related fields. This is an introductory course and will contribute to upskilling of the entire construction sector, thereby increasing the industry's international competitiveness while also providing important prerequisites for the development of future sustainable, beautiful, and inclusive cities. Since the course is open to everyone, we hope that more groups, such as students, doctoral candidates, forest owners, and others with an interest in forestry, will take the course and engage with inspiring lectures where scientific knowledge primarily produced within SLU (Swedish University of Agricultural Sciences) is presented.
About the courseRenewable hydrogen stands out as a highly promising solution to decarbonize heavy industries and transportation sector, helping to achieve the climate goals of Sweden- reaching net zero emissions by 2045. The terms renewable hydrogen, clean hydrogen or green hydrogen refers to hydrogen produced from renewable energy or raw material. The utilization of renewable hydrogen for industrial applications necessitates the development of the entire value chain, from generation and storage to transport and final applications. Unlocking the potential of hydrogen economy in Sweden involves not only technological advancements and infrastructure development but also a skilled workforce. This course offers an introduction of renewable hydrogen as a pivotal component for industrial applications, focusing on its generation, storage, transport, and utilization within industrial contexts. Participants will gain a comprehensive understanding of the technical, economic, and environmental aspects of renewable hydrogen technologies, such as electrolysis, fuel cell, and hydrogen storage and distribution solutions, preparing them with essential knowledge and foundational insights for advancing the decarbonization of industrial processes through the adoption of hydrogen-based energy solutions. Aim and Learning OutcomesThe goal of this course is to develop a basic understanding of renewable hydrogen as a pivotal component for industrial applications, focusing on its generation, storage, transport, and utilization within industrial contexts.The learning outcomes of the course are to be able to: Explain the fundamental knowledge and theories behind electrolysis and fuel cell technologies. Compare and describe the differences of existing renewable hydrogen generation technologies (PEM, AE, AEM, SOE, etc.), and existing fuel cell technologies (PEMFC, MSFC, SOFC, etc.. Describe the principles of hydrogen storage, including gas phase, liquid phase, and material-based storage and thermal management of storage systems. Identify the challenges of hydrogen transportation and be able to describe relevant solutions. Examples of professional roles that will benefit from this course are energy and chemical engineers, renewable and energy transition specialists, policy makers and energy analysts. This course will also support the decarbonization of hard-to-abate industries, such as metallurgical industry and oil refinery industry, by using renewable hydrogen. This course is given by Mälardalen university in cooperation with Luleå University of Technology. You may join the course from March 17 until the middle of April, 2025. Scheduled online seminars April 22nd, 2025May 19th, 2025 Study effort: 80 hours
Målet med kursen är att ge lärare fortbildning inom ämnet djurvälfärd och hållbarhet. Kursens mål är också att ge lärare inspiration att designa sin egen undervisning, att ge lärare möjlighet att ta till sig ny forskning och att dela med sig av läraktiviteter som kan användas av fler.