This course explores how we can design, create and achieve climate neutral cities. We embrace the “mission to the moon” approach for tackling greenhouse emissions from cities putting an emphasis on pathways and opportunities. We utilise insights and inspiration from Sweden, Europe and around the world.
We target how to support individuals and organisations in developing transformative skills and capacities for action on climate neutral cities. We focus on mitigation of greenhouse gas emissions but also connect to adaptation, resilience, social justice and sustainable development in the context of cities, climate and change.
The course is designed around 5 interconnected modules. We therefore created a format that provides a diversity of ways to learn and creatively engage with the content.
Module 1: Visions and Plans. In this week we begin with looking at visions for climate action and the plans or strategies on how to achieve ambitious goals.
Module 2: Data and Tools. In this week we explore tools for climate action and creating both immediate and long-lasting impacts.
Module 3: Finance and Partnerships. In this week we tackle the key challenge of financing climate action and the vital role of partnerships.
Module 4: Engagement and Action. In this week we delve into community and citizen engagement and how it underpins climate action.
Module 5: Research and Innovation. In this week we connect climate action to research, evaluation and innovation.
This course will soon be available
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.
This course provides a fundamental knowledge of IoT, targeting physical devices, communication and computation infrastructure. The course gives theoretical knowledge as well as hands-on experiences to build an IoT application.
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.
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.