Linnaeus University is located in Växjö and Kalmar and offers over 150 degree programmes and 1300 single-subject courses. Students can study different subjects within arts and humanities, health and life sciences, the social sciences, the natural sciences, technology, and business and economics. There are also a number of different contract educations, like the headmaster training and police education. Linnaeus University is a creative and international knowledge environment fostering curiosity, new ideas and an added value. We are working with competency development for professional with the life long learning. There are 33,000 registered students at Linnaeus University
Industry leaders can greatly benefit from learning about agile working methods as it can contribute to increased productivity, customer focus, flexibility, engaged employees and innovativeness. By using agile working methods, an organization can become more efficient and adaptable, which can increase its success in the market. Target groupThe course is aimed at people in a management function (managers, middle managers, team leaders, project managers, etc.) mainly in industry who are interested in learning more about agile working methods. ContentTraditional organizations tend to get clogged over time and inefficient. To mitigate this there is a need for agile organization that rely less on legacy structures and processes and much more on updating and optimizing processes to facilitate better work. In this manner agile organizations become responsive and adaptable to the changes accruing around them. For achieving the agile transition organizations need agile methods. This course is targeted for managers within the digitalized industry sector. The course covers the following areas: Foundations of agile methods. Case studies of practical examples of agile adoption in industrial settings. What industry managers should know about agile approach. Assessment methods of agile readiness of the digitalized industrial organization. Strategic thinking and roadmap development for agile transition. The goal of the course is that the participants should be able to: Describe and understand the core principles of agile methods. Understand the possibilities, challenges, and issues while adopting agile methods in industrial organizations. Identify the areas with the digitalized industry sector where agile approaches can be utilized and how can be adopted. Assess and develop a strategy and roadmap for implementing agile ways of working in the digitalized industry. The course is offered in collaboration with Combitech through Stefan Aleborg who has long experience of working with agile methods in different type of organizations. Practical informationThe course is primarily based on the flipped classroom approach with three on-site workshops. Materials will be provided in a form of pre-recorded and online lectures, online guest lectures, reading materials, and scientific articles. The course is assessed through 3 mandatory assignments, mandatory seminars, and active participation in discussions forum and workshops. Teaching language: lectures and materials can be in English, but the physical meetings will be held in Swedish. 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 and gives 3 ECTS course credits
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
Maybe you want to connect monitoring to a truck, or why not build a connected pump control? Do you want to measure temperatures, pressures or vibrations? Do you want knowledge about how to connect one of your existing products? Then this course is for you. Do you work as an engineer in the industry and want to learn how to develop an idea with IoT? Do you work as a developer at an IT company and want to learn more about the hardware and the entire infrastructure within IoT? The course is primarily aimed at those who are professionals in the engineering profession, but you do not need to be either a programmer or an electronics engineer to take advantage of the course. The content is adapted so that you can work with your specific ideas. The course is focused on providing both theoretical and practical knowledge in the field of Internet of Things. You will gain knowledge of the area's applications and definitions, and you will learn how to build an IoT device, all the way from hardware to visualization. You will have the opportunity to practically work with hardware, sensors, as well as infrastructure and security. We will work with, among other things, WiFi, BLE, LoRaWAN, SigFox, NB-IoT / LTE-M1, as well as insight into how data is transported throughout from the device to the database and then to the application. The course will be held mostly at a distance with a couple of scheduled workshops (13/9, 6/10, 27/10) either on site or online. All lectures will be available online. The course will be delivered in a flexible way to facilitate the combination of coursework with your ongoing professional commitments. You will need to buy IoT hardware before the start of the course, the cost can be different depending on the type of project, guide value is approx: SEK 1,000. The total scope of the course is normally about 80 hours.Language of instruction: EnglishThe course is free of charge
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
In a data-driven world, it is important to be able to analyze large amounts of data to identify patterns of interest and test hypotheses about them. Visual Analytics provides us with an interactive process of analytical reasoning facilitated by data visualization, combining the strengths of humans and computers in order to derive insight from massive, dynamic, ambiguous, and often conflicting data. In this course we will introduce basic concepts of data visualization, how to apply them to build interactive interfaces for data sets of different types, and which tools are useful in this process. Target group This course is for experienced developers working in the industry with an interest in data analysis and visualization. Content Foundations of perception and design that are important for creating new visualizations.Comparison between different types of visualization that work better for different types of data.Integration of multiple individual visualizations into interactive dashboards.Overview of the exploratory visual analysis process that incorporates all the above into a unified pipeline.Practical applications using interactive visualization libraries. Practical information All materials will be available digitally, including reading materials, lecture slides, videos, practical exercises, etc. The course will be given in a flexible manner to facilitate the combination of course work with your professional commitments. We recommend that you work on a project during the course that you can use in your daily work, with your own data, and your own problems. Entry requirements The basic eligibility for this course is a Bachelor degree. Candidates with relevant work experience are also invited to apply. Two years of relevant work experience is considered equivalent to one year of university studies at the Bachelor level.
Smart maintenance means using advanced technologies and data to optimize and streamline the company's maintenance processes. By investing in this skill, a leader can not only understand and apply the latest innovations in the maintenance industry, but also increase company productivity, reduce costs and ensure long-term sustainability. This smart maintenance course provides a leader with the tools and knowledge needed to navigate the digital era and maximize business reliability and performance. Target group The course is aimed at technical managers and people with a leading position in producing companies. The course is also suitable for those who are responsible for maintenance and operational safety, for example in the role of maintenance engineer, maintenance coordinator or maintenance manager. It is also aimed at you who are responsible for and work with overall sustainability, quality and safety issues. Content The course consists of three parts. Part 1 - In the first part (w. 12–14) we focus on technology solutions and how these are used to achieve smart maintenance. You will gain a practical understanding of how the technology works and what possibilities and limitations they have. We also describe the basics of predictive maintenance. Part 2 - The second part (w. 15–17) focuses on information needs for smart maintenance and how this can be ensured with technology solutions. You do exercises where you get to define what data and information is needed to plan, prepare, implement and follow up smart maintenance and then identify how you get access to this data. Part 3 - The third part (w. 18–20) addresses how a digitization strategy can be established for the maintenance organization. Practical information The course alternates theory with practical examples and exercises. The individual tasks give you the opportunity to work with the course content in a practical way in your own business. The course literature is in both English and Swedish and includes both popular science texts and research articles. The language of instruction is primarily Swedish. Entry requirements The basic eligibility for this course is a bachelor's degree in Mechanical Engineering or equivalent. People with relevant work experience are also welcome to apply. Two years of relevant work experience is considered equivalent to one year of university studies at bachelor's level.