This course makes you acquainted with the concept of systems-of-systems (SoS), which means that independent systems are collaborating. It gives you an understanding why SoS is an important topic in the current digitalisation and provides a theoretical and practical foundation for understanding important characteristics of SoS. It also gives you a deeper knowledge in a number of key concerns that need to be considered when engineering SoS.
Admitted students to this course may join the course any time between August 30 and October 24, 2021. With the recommended study pace of 25%, the course would take approximate seven calendar weeks to complete. Higher or lower study pace is possible as long as the course is finished no later than January 16, 2022.
This course deals with model-based testing, a class of technologies shown to be effective and efficient in assessing the quality and correctness of large software systems. Throughout the course the participants will learn how to design and use model-based testing tools, how to create realistic models and how to use these models to automate the testing process in their organisation.
In this course you will learn state-of-the-art statistical modelling for the purpose of analysing industrial data. The course also presents the basics of relational databases and data manipulation techniques needed to prepare the data for analysis.
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.
In this course, you will learn about common air pollutants and how to manage and control air pollution. The course gives you enhanced knowledge about relevant aspects of modern air quality management systems based on regulations and policies related to ambient air quality management in the EU and Sweden.
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.