Our 20,000 students read courses and study programmes in Business, Health, Engineering and Education. We conduct research within all areas of education and have internationally outstanding research in future energy and embedded systems. Our close cooperation with the private and public sectors enables us at MDU to help people feel better and the earth to last longer. Mälardalen University is located on both sides of Lake Mälaren with campuses in Eskilstuna and Västerås.
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Would you like to know what Industry 4.0 is about? Then this course is for you! In the course, we look at enabling technologies of Industry 4.0 from a human and industrial perspective. The course covers many topics and you will learn the basic terminology related to Industry 4.0 as well as insight and understanding of the Fourth Industrial Revolution and how it is set to affect industry and individuals.
The information and communication technology (ICT) sector is responsible for approx. 1.8-2.8% of the global greenhouse gas (GHG) emissions in 2020, and software is both part of the problems and the solutions. Traditional software engineering principles and techniques do not consider the climate, environment, and sustainability aspects in building and using software for any purpose. We, software engineers, developers, researchers, climate scientists, and various other related stakeholders, need to think about how we can reduce the carbon footprint due to building and using software-intensive systems. Green and sustainable software engineering is an emerging concept that can help reduce the carbon footprint related to software. In this introductory course, we will introduce the concept of green and sustainable software engineering and the engineering process to build green and sustainable software. Topics Sustainable and green computing Sustainable and green software engineering Process Energy efficient computing Sustainability issues in Scientific computing You will learnBy the end of the course, you will be able to: analyze the green and sustainability issues in traditional software engineering, identify and incorporate key elements to be included in the software engineering process to make the software green and sustainable, and use techniques to make your software code energy efficient. Who is the course for?This course is designed for those who are software developers, managers and software related policy makers, or have knowledge about software development, and want to consider the green and sustainability aspects in their everyday life. Also, this course will be useful for computational scientists who build green software and want to know more about these aspects in software engineering. However, this is an introductory course, and it will show a path for life-long learning to build more in-depth knowledge in each concept introduced in this course.
Do you want to learn the basics of Industry 4.0, at your own pace, whenever you want? Then the MOOC (Massive Open Online Course) Introduction to Industry 4.0 is for you. You will learn basic terminology and theory while gaining insight and understanding of the fourth industrial revolution and how it affects us. The MOOC: Introduction to Industry 4.0 is part of MDU's investment in smart production. The course is divided into ten modules, each of which describes different technologies in Industry 4.0. We estimate that it will take about 40 hours to complete the course and it is in English. The MOOC can also give you eligibility to apply for these 3 university courses at Mälardalen University: Internet of things for industrial applications, 5 credits Simulation of production system, 5 credits Big data for industrial applications, 5 credits
Do you want to be efficient, effective and minimize waste by learning and implementing lean production tools? This course provides insight into the demands and challenges posed by competitive production in industrial production systems and develops your ability to participate in and to drive improvement work. The course focuses on efficient lean production. Through theory and project work, you will learn useful techniques, methods and strategies. You will obtain the necessary knowledge and training to carry out value stream mapping and other forms of improvement work. The course offers current and competitive knowledge through its close links with our successful research and partner companies. It provides basic knowledge and understanding of the modern view of lean production in industrial activity.
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 has the objective to provide proficiency in cybersecurity analysis and design in industrial settings, with a special focus on smart factories and Industry 4.0. To that aim, you will learn about advanced cybersecurity concepts, methodologies and tools. You will also be able to apply your knowledge to case-studies of industrial relevance.
The aim of this course is to provide participants with the principles behind model-driven development of software systems and the application of such a methodology in practice. Modelling is an effective solution to reduce problem complexity and, as a consequence, to enhance time-to-market and properties of the final product.
The course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modeling
The aim of the course is to introduce the participants into methods and tools for verifying systems that need to react to external stimuli. The methods use system models with precise formal semantics and will span model-checking as well as deductive verification. A set of simple examples as well as real-world applications will be used throughout the course to illustrate the methods and their tool support. The objective of the course is to understand the underpinning theories of formal verification, and learn how to apply tool support in order to verify system models.
The aim of this course is to give students insight about certification and about what it means to certify/self-assess safety- critical systems with focus on software system and to create a safety case, including a multi-concern perspective when needed and reuse opportunities, when appropriate.
This course deals with model-based testing, a class of technologies shown to be effective and efficient in assessing the quality and correctness of large software systems. Throughout the course the participants will learn how to design and use model-based testing tools, how to create realistic models and how to use these models to automate the testing process in their organisation.
This course provides an understanding of the fundamental problems in software testing, as well as solid foundation in the practical methods and tools for a systematic state-of-the-art approach to testing of software.