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.
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.
Do you want to be efficient, effective and minimize waste by learning and implementing lean production tools? This course provides insight into the demands and challenges posed by competitive production in industrial production systems and develops your ability to participate in and to drive improvement work.
The course focuses on efficient lean production. Through theory and project work, you will learn useful techniques, methods and strategies. You will obtain the necessary knowledge and training to carry out value stream mapping and other forms of improvement work.
The course offers current and competitive knowledge through its close links with our successful research and partner companies. It provides basic knowledge and understanding of the modern view of lean production in industrial activity.
In the modern IT world, businesses often have access to large amounts of data collected from customer management systems, web services, customer interaction, etc. The data in itself does not bring value to the business; we must bring meaning to the data to create value. Data mining and machine learning is an area within computer science with the goal of bringing meaning to and learning from data.
This course will focus on applied machine learning, where we learn what algorithms and approaches to apply on different types of data.This course is for experienced developers working in the industry. The course includes the following: Supervised learning, different types of data and data processing, Algorithms for handling text documents, Algorithms for handling data with numerical and categorical attributes, Neural Networks and Deep Learning for image recognition
Would you like to know what Industry 4.0 is about? Then this course is for you!
In the course, we look at enabling technologies of Industry 4.0 from a human and industrial perspective. The course covers many topics and you will learn the basic terminology related to Industry 4.0 as well as insight and understanding of the Fourth Industrial Revolution and how it is set to affect industry and individuals.
Answer Set Programming (ASP) is a declarative programming paradigm designed within the field of Artificial Intelligence (AI), and used to solve complex search-problems. The declarative nature of ASP allows one to encode a problem by means of logic. In this way, unlike in imperative programming approaches, there is no need to design an algorithm as a solution for the given problem. In this sense, ASP is comparable with SAT-based encoding or constraint satisfaction problems. However, due to its stable-model semantics, ASP provides a richer representation language useful to handle uncertain situations more effectively for real world scenarios. The advantages of declarative programming together with non-monotonic nature of ASP in handling uncertainties have recently made ASP more attractive both for academia and industry. This course focuses on formalizing and solving various search problems in planning, scheduling and system configuration in ASP.