COURSE DESCRIPTION
In this course package you will get a basic introduction to the concept of sustainable development. Among other things, we will discuss:
You will also learn about key competences for sustainability such as systems thinking and values thinking, and get an overview of the basic mechanisms of Earth’s climate and climate change.
The aim of this course is to provide participants with the principles behind model-driven development of software systems and the application of such a methodology in practice. Modelling is an effective solution to reduce problem complexity and, as a consequence, to enhance time-to-market and properties of the final product.
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.
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 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.
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.
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