Mälardalen University

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.

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.

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.

The course gives an introduction to how CAD (computer-aided design) can be effectively utilized as an aid in mechanical engineering or product development. Both as a tool for design and visualization and also to create production data in the form of technical drawings. The aim is to give you basic skills in creating three-dimensional models and two-dimensional drawings both at the detail and product level, as well as knowledge of the rules and standards needed both to interpret and create technical drawings.

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.

In this course, you will be made aware of the state-of-the-art in cybersecurity research and state of practice in industry. Cybersecurity vulnerabilities are a threat to progress in the business sector and society. This is an accelerating threat due to the current rapid digitalisation, which in manufacturing is termed Industry 4.0. Companies are aware of this threat and realise the need to invest in countermeasures, but development is hampered by lack of competence.  

Do you want to deepen your knowledge in Industrial Internet of Things? In this course, you will gain deeper knowledge and understanding of the Industrial Internet of Things (IIoT), platforms and cloud services used in manufacturing industries. You will learn to understand the use of IoT platforms and how to design and implement simple systems and how to create value by using IoT solutions within industrial systems. The course will provide you with practical and theoretical knowledge in IIoT, platforms and cloud services as well as in-depth knowledge in production, logistics and product development.

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

This course provides a fundamental knowledge of IoT, targeting physical devices, communication and computation infrastructure. The course gives theoretical knowledge as well as hands-on experiences to build an IoT application.

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.