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.
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.
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.
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 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.
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.