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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This course provides an understanding of automating software testing using program analysis with the goal of intelligently and algorithmically creating tests. The course covers search-based test generation, combinatorial and random testing while highlighting the challenges associated with the use of automatic test generation. You will learn: Understand algorithmic test generation techniques and their use in developer testing and continuous integration. Understand how to automatically generate test cases with assertions. Have a working knowledge and experience in static and dynamic generation of tests. Have an overview knowledge in search-based testing and the use of machine learning for test generation.
The main goal of this course is to teach you basic knowledge and skills in argumentation.You will be engaged in co-constructing evidence-based justifications as well as in analyzing existing justifications in search of argumentation fallacies. Individual work as well as group-based work will allow you to practice. You will analyze climate-related articles (published in scientific literature but also in the news) and will extract the implicit underlying arguments and provide their analysis.Ultimately, this course will help you to develop basic argumentative skills needed to critically join the debate in society on climate goals. Who is the course for?CLIMATE GOALS, ARGUMENTATION, EVIDENCE is aimed at anyone who is interested in moving the first steps into the argumentation domain with the purpose of joining the debate on climate goals.An engineer (but also a politician) is expected to have founded arguments before taking any (climate-related) action. A citizen is expected to have founded arguments before engaging and sustaining any climate-related political agenda. How is the course structured?The course is a 4-week course. Each week mainly focuses on a single Intended Learning Outcome.
This course will provide a basic theoretical and practical knowledge in the art of configuring and securing computer networks and create simpler topologies. Together with the "Computer Networks II" distance course (Datakommunikation i nätverk II, distanskurs) you will be covering most, but not all, of the content that are part of a Cisco Certified Network Associate (CCNA) certificate. The certificate is not part of this course.
In this course, you will learn how data analysis in virtual production can improve your organization's results! Data analytics in virtual production uses advanced techniques to collect, analyze and present data to improve production. This system is designed to help companies optimize their production and increase efficiency. By learning how to model, do scenario analysis and evaluate using industrial software, identify bottlenecks, and use AI methods and applications, s necessary to succeed with a full production analysis. The course is given with flexible start and study pace, but we recommend a study pace of 20 %, which means that the course takes about 8 calendar weeks.
Numerical models are used in every engineering task, from conceptual design to optimization, control, and diagnostics. As the process becomes more complex, data driven models are a powerful tool that allows to quantify relationships between available data and observations, which forms the basis for machine learning. Image recognition, spam filtering, and predictive analytics are some examples of how we can use data driven models. This course provides a simple introduction to fundamental techniques for dimensionality reduction, classification, and regression, which can be applied to all types of engineering problems.
This course will teach you how to build convolutional neural networks. You will learn to design intelligent systems using deep learning for classification, annotation, and object recognition.
Learn about digital twins and how they can be used in smart production! A digital twin is used to create a virtual model of a real production system. Among other things, it can be used to simulate how the product will be manufactured, how materials flow and how machines move. The course gives you knowledge of industrial digital twins and their application within the framework of smart production. The course is given with flexible start and study pace, but we recommend a study pace of 20%, which means that the course takes about 8 calendar weeks.
In this course you will learn how to design production systems using XR. By visualizing production processes using various XR technologies, you will gain an understanding of when each technology is best suited and how it can be implemented.
Today, many industries face an increase in the design of dependable systems, often with a multitude of challenges including more complex electronics and intensive software. At the same time, most of the engineers graduating from universities do not have skills in designing fault tolerant systems. This online course aims to give engineers and students a toolbox of fail-safe design concepts, addressing both hardware and software techniques, such that they can understand the rationales for suitable mitigation strategies.