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.
The emergence of artificial intelligence has created a new opportunity to apply machine learning (ML) in industry 4.0. In this era of the Internet of Things and Big data, processing of a large amount of data would not be possible without ML. Thus, ML made industrial production smarter than ever before. So, learn the course “Machine learning for Industry 4.0” to bring in new business models in your company and boost productivity using ML.
The course provides knowledge about basics of ML and data, describes ML algorithms and tools and also explains the concept of Industry 4.0 and digitalization in industry 4.0. The individual processes can be better understood and optimized with the help of the knowledge from the course. Also, it could have an important contribution in analysing the industrial data set, improving results, and making decision and/or predictions for failure, demand, sales, and production.
This course is a collaboration between Högskolan Väst, Linnéuniversitetet and Mälardalens Högskola. It consist of three course modules: Introduction to Machine Learning (MDH – 2 credits, Basic level), Industry Digitalization – Industry 4.0 (HV – 2,5 credits, Advanced level), Applied Machine Learning (LNU – 3 credits, Advanced level). Students who pass all three courses will receive a diploma from Learning for Professionals.
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.
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
This course, Digitally-enabled production, is offered in a collaboration between Mälardalens högskola (MDH), Högskolan Väst (HV) and Linnéuniversitetet (LNU).
The course aims to support and facilitate our partner manufacturing companies to become competitive in digitally-enabled production. During the course, we address the potential prerequisites and capabilities required for implementing industry 4.0 in the context of an overall production system. More specifically, we increase the competence base of companies in three areas—internal logistics systems, virtual factory, and sensor and signal processing—which can holistically interconnect the key components for the successful implementation of industry 4.0.
This course consists of three interconnected course modules at an advanced level and it is offered between September and November 2020:
Internal Logistics in Industry 4.0, 2.5 credits, MDH, https://www.mdh.se/en/malardalen-university/education/course-syllabus?id=29594
Virtual Factory and Robot Cell Simulation, 2.5 credits, HV, https://admin.hv.se/samverka-med-oss/kompetensutveckling/teknik/kompetensutveckling-inom-produktionsteknik/virtual-factory-and-robot-cell-simulation/
Data Acquisition and Monitoring, 2.5 credits, LNU, https://kursplan.lnu.se/kursplaner/kursplan-4MT017-1.pdf
More information about the course is available on the below link:
Apply to the course in the below link:
Örebro University is offering a course on Mixed Reality for Industrial Applications. This course looks into different phenomena of human interaction with mixed reality. We will examine different aspects of human perception of mixed reality, depending on such factors as fidelity, immersion, and presence.
In the course we look at the way people act when being immersed into virtual or remote environment. And we look at the methods of building efficient interaction scenarios and measuring interaction quality, using qualitative and quantitative tools. Upon completion of this course, students will be able to apply theoretical knowledge on developing mixed reality experiences to appropriate industrial problems and evaluate the effect of mixed reality in a critical manner. The course is part of the education initiative Smarter at Örebro University.