COURSE DESCRIPTION
This course looks at where important materials in products we use every day come from and how these materials can be used more efficiently, longer, and in closed loops. This is the aim of the Circular Economy, but it doesn’t happen on its own. It is the result of choices and strategies by suppliers, designers, businesses, policymakers and all of us as consumers.
In addition to providing many cases of managing materials for sustainability, the course also teaches skills and tools for analyzing circular business models and promotes development of your own ideas to become more involved in the transition to a Circular Economy. You will learn from expert researchers and practitioners from around Europe as they explain core elements and challenges in the transition to a circular economy over the course of 5 modules:
Module 1: Materials. This module explores where materials come from, and builds a rationale for why society needs more circularity.
Module 2: Circular Business Models. In this module circular business models are explored in-depth and a range of ways for business to create economic and social value are discussed.
Module 3: Circular Design, Innovation and Assessment. This module presents topics like functional materials and eco-design as well as methods to assess environmental impacts.
Module 4: Policies and Networks. This module explores the role of governments and networks and how policies and sharing best practices can enable the circular economy.
Module 5: Circular Societies. This module examines new norms, forms of engagement, social systems, and institutions, needed by the circular economy and how we, as individuals, can help society become more circular.
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 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 purpose is to give the students an overview of issues and methods for development and assurance of safety-critical software, including details of selected technologies, methods and tools. The course includes four modules: Introduction to functional safety; knowledge that give increased understanding of the relationship between Embedded systems / safety-critical system / accidents / complexity / development models (development lifecycle models) / certification / “the safety case”. Analysis and modelling methods; review of analysis and modelling techniques for the development of safety-critical systems. Verification and validation of safety critical software, methods and activities to perform verification and validation. Architectures for safety critical systems. Safety as a design constraint.
The purpose of the course “Artificial Intelligence for Managers” is to give managers and decision makers a principle understanding of AI and to increase their understanding of opportunities, difficulties, benefits, and risks connected to AI. It is neither an “Introduction to AI” nor an “AI for dummies” course. Instead, it is set to demystify AI and to transform it into an actionable tool for manages and decision makers. Target groupThis course is for product managers, project managers, executives, and engineering managers in organizations that have already made, or are about to make, the transition to working with AI. ContentThe course is organized in three modules. The initial module will focus an introduction to AI, giving an understanding of what type of cases can be addressed with AI and what managers need to know about AI technology. Module two will cover tools and concrete on how to set up an AI strategy and roadmap, how to get started on AI projects, how to integrate AI and IT development, how to (self) evaluate AI in use, and, not to forget, the ethical and legal aspects of AI. The third module will give the participants the chance to use their new knowledge and tools and work with their own practical cases and how they could be addressed using AI. The goal of the course is to empower the participants to: Describe the principal concept of AI, its strengths, and shortcomings Understand opportunities, myths, and pitfalls of AI Identify problem areas in industry, society, and in management where AI could be utilized Analyze how AI can be applied in a particular problem area Manage an AI strategy and get started: implement a strategy and a roadmap to apply AI in a particular problem area Understand how to integrate AI with IT development Assess the maturity of AI utilization in an organization Reflect on applications of AI from an ethical and legal perspective as well as the future challenges (technical, organizational, social, etc.) Practical informationAll materials will be accessible and include reading material, lecturer slides etc. The lectures can either be attended live via Zoom or later using the recordings at a time that is convenient for the participants. There will be 3 onsite workshops with a focus on interaction with the teacher and the co-participants of sharing real-life experiences and insights. The course will be delivered in a flexible manner to facilitate the combination of course work with your ongoing professional commitments. The total effort to pass this course is typically around 200 hours. Teaching language: English Entry requirementsThe basic eligibility for this course is a bachelor’s degree. Candidates with corresponding work experience are also invited to apply. Two years of relevant work experience is considered equivalent to one year of university studies at bachelor level. The course is free
In this course, you will be made aware of the state-of-the-art in cybersecurity research and state of practice in industry. Cybersecurity vulnerabilities are a threat to progress in the business sector and society. This is an accelerating threat due to the current rapid digitalisation, which in manufacturing is termed Industry 4.0. Companies are aware of this threat and realise the need to invest in countermeasures, but development is hampered by lack of competence.