-
DURATION14 HOURS
-
SUBJECT AREAClimate Transition
Individual & Society -
COURSE LEVELMOOC
-
CREDITS0.0 HP
-
INSTITUTIONSLund University
Open for the Climate
-
STUDY TYPEMOOC
COURSE DESCRIPTION
How can we work with nature to design and build our cities?
This course explores urban nature and nature-based solutions in cities in Europe and around the world. We connect together the key themes of cities, nature, sustainability and innovation. We discuss how to assess what nature-based solutions can achieve in cities. We examine how innovation is taking place in cities in relation to nature. And we analyse the potential of nature-based solutions to help respond to climate change and sustainability challenges.
This course was launched in January 2020, and it was updated in September 2021 with new podcasts, films and publications. The course is produced by Lund University in cooperation with partners from Naturvation – a collaborative project on finding synergies between cities, nature, sustainability and innovation. The course features researchers, practitioners and entrepreneurs from a range organisations.
courses you may also like
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 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.
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.
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 may join the course any time between September 2 and October 6, 2024. 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 19, 2025.