In the modern IT world, businesses often have access to large amounts of data collected from customer management systems, web services, customer interaction, etc. The data in itself does not bring value to the business; we must bring meaning to the data to create value. Data mining and machine learning is an area within computer science with the goal of bringing meaning to and learning from data. This course will focus on applied machine learning, where we learn what algorithms and approaches to apply on different types of data.This course is for experienced developers working in the industry. The course includes the following: Supervised learning, different types of data and data processing, Algorithms for handling text documents, Algorithms for handling data with numerical and categorical attributes, Neural Networks and Deep Learning for image recognition

Do you want to deepen your knowledge about maintenance and dependability? Then this course is for you. The course focuses on the value of dependability in production systems and how maintenance contributes to the achievement of optimal dependability. A well-designed maintenance programme starts with the design of the production system, from the procurement of new equipment, to system service life.  

The manufacturing industry collects increasingly large volumes of big data, that is, data at high speed, generated from a wide range of sources in different formats and quality levels. But what is data without insight? This course will help you master the fundamental concepts of big data, cloud computing and smart decision-making for industrial analytics. Designed specifically for manufacturing sector professionals, this Master’s course provides knowledge and insights in handling and processing data, using machine learning and data analytics in the cloud environment. You will learn machine learning-based solutions for industrial applications, such as smart decision-making and predictive maintenance, using state of the art cloud platform tools.

Med produktionslogistik menas planering, samordning och styrning av det tillverkande företagets materialflöden och resursflöden med utgångspunkt från dess produktionssystem. Området har fått allt större betydelse för företag i takt med dels ökade krav på kortare och säkrare leveranstider, dels ökade krav på mindre kapitalbindning samtidigt som produkter ska kundanpassas.

Kursen fokuseras på grundläggande metodik för den virtuella fabriken inom konceptet industrins digitalisering.  Koncepteten virtuella fabriker, fabriksskanning och AR/VR (Augmented och Virtual Reality) kopplat mot industrins digitalisering tas upp i kursen och diskuteras. Andra moment som diskuteras är databassystem kopplade mot simuleringsprogramvara samt autonoma robotceller.

Berör några av de grundläggande koncepten och teorierna kring strategisk teknologihantering och granskar viktiga strategiska beslut i centrum av teknik- och innovationshantering utifrån företagets konkurrenssituation. Dessa kan till exempel beröra valet av teknologi, disruptiva innovationer, tidpunkten för teknikutvecklingsinitiativ, implementeringsstrategier, modulär design, skapande av strategiska partnerskap eller anpassning till snabb teknisk förändring.

Kursen lyfter fram hur konstruktiva utformningar av produkter för att dessa skall kunna tillverkas med additiva metoder. Vidare innehåller kursen programmering av processparametrar och hur dessa påverkar metallurgi och hållfasthet hos de tillverkade objekten. Dessutom fokuseras olika metoder för inspektion och validering, samt kostnadskalkylering utifrån ett globalt perspektiv inkluderande miljö- och hållbarhetsaspekter.

Kursen lyfter reparationsmetoder baserade på pulverbeläggning med laserteknik eller termisk sprutning. I kursen analyserar vi olika metoders tillverknings- och affärsmässiga aspekter. Vi diskuterar materialkarakterisering, kvalitet och struktur för de pålagda reparationsskikten och reflekterar kring olika metoder för inspektion och kvalitetskontroll av de reparerade produkterna.

Reinforcement Learning (RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences. The course is part of the education initiative Smarter at Örebro University. This is course requires completion of course Reinforcement Learning part 1.  Read more

Örebro University is offering an introduction course in artificial intelligence. The course will address the basic concepts within classical artificial intelligence (other than machine learning). Traditional artificial intelligence is characterized by the so-called declarative approach to problem solving. The course deals with a selection of different intelligent problem-solving methods, both in theory and practice. After completing the course, the student will be able to model and use appropriate generic solution algorithms to solve problems in an intelligent system. The course is part of the education initiative Smarter at Örebro University. Read more

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

The course will present real-world applications of control methods for energy processes and power plants. Practical considerations will be made on selecting the best control architecture and including modifications to improve control response.

The purpose of the course is to increase your knowledge in the field of applied statistics. The course will illustrate how to reach statistically justified conclusions based on common statistical methods, such as statistical inference, analysis of variance, correlation and regression. The course will provide opportunities to become familiar with the concepts of understanding statistics and challenging assumptions. During the course we will discuss the role of statistics in engineering and science, statistical thinking and management of large data sets.

The important part of the course will be focused on addressing real industrial and environmental challenges by employing state-of-the-art spectroscopic material characterization methods for process monitoring, control and optimization.

In this course we will discuss the need for experimental measurements in fluid mechanics and heat transfer, the challenges involved, and how to choose the best method for each application. You will learn about commonly used methods to measure the flow of gases and liquids. You will also learn about methods to measure heat transfer, which is relevant for cooling of high temperature parts in small and large engines for power generation.

In this course you will learn about the most common air pollutants and their emission. You will learn how to monitor, assess and model the distribution of air pollution, and how to control emissions from motor vehicles and stationary sources.

The course addresses the concept of circular economy, its use and limitations in the field of environmental engineering, methods for the assessment of resource efficiency, sustainability and environmental impact and practical examples related to waste management.

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.

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.

The course aims to provide students an opportunity to develop skill in experience design and design thinking. The Usability and User Experience course focuses on the design process, techniques and methods to design and produce digital artifacts with desirable experiential qualities.