learning for professionals

Mälardalen University

Our 16,000 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 Mälardalen with campuses in Eskilstuna and Västerås.

9 RESULTS

Digital twins, XR and AI for Industry 4.0

By taking part in this course you will learn about the role of visualization in industrial applications with a specific focus on Industry 4.0. You will learn how to evaluate and develop production systems and processes that integrate visualization technologies, such as digital twins, virtual and augmented reality and are supported by artificial intelligence.

Industrialization and Ramp-up in Industry 4.0

You will learn methods, tools, and strategies for your company to gain a world class competence in the industrialization of new products and production technologies. If you are involved in the activities of industrialization, product or process introductions, and integration of new products and/or production technologies, then this course is for you.

Industry 4.0 - Introduction

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.

Industry 4.0 - Optimization of Production Systems

Advance your skills in simulation and optimization! This course aims to provide knowledge on how different methods can be applied to optimize production systems. We will begin with the concept of optimization theory, and then start building simulation models of production systems. After that, we will practice different methods to optimize production systems.  

Industry 4.0 - Realisation

The course covers digitalisation and automation technologies and their application in smart factories. Technologies covered include simulation and deployment, digital twin, connectivity as an enabler for e.g. predictive maintenance, manufacturing execution systems and robotics.

Introduction to Machine Learning

Today, the explosion of data has created new opportunities to apply machine learning (ML). Handling of the large amounts of data created by the very rapid digitization would not be possible without Machine Learning (ML). The purpose of the course "Introduction to Machine Learning" is to give you the foundation for ML. You will get an introduction to the basic areas of ML: data, statistics and probability for ML.

Quality assurance - Certification of safety-critical (software) systems

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.

Quality assurance - The applied science of software testing

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.

Smart Logistics

Are you working with logistics in the manufacturing industry? Then this is a course for you! The course is specially designed for those who work with logistics in the manufacturing industry and it will give you an increased understanding of how to design smart logistics systems. You will get to analyse your company's logistics system and with the help of various Industry 4.0 technologies you will identify possible ways to improve the logistics system of your own company.