MACHINE LEARNING FOR INDUSTRY 4.0

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.

In contrast to learning how to do manual testing, in this course you will learn how to generate tests automatically in the sense that test creation satisfying a given test goal or given requirement is performed automatically. 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.

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.

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 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: https://www.mdh.se/en/malardalen-university/education/further-training/smart-production/digitally-enabled-production-7.5-hp Apply to the course in the below link:  https://www.mdh.se/en/malardalen-university/education/further-training/smart-production/digitally-enabled-production-7.5-hp/application-form-digitally-enabeled-production-7.5-hp