ENGINEERING DRAWING AND CAD

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.

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 

The aim of this course is that students will learn about the analysis, design, and programming of deep learning algorithms. The course is part of the programme MAISTR (hh.se/maistr) where participants can take the entire programme or individual courses. The course is for professionals and is held online in English. Application is open as long as there is a possibility of admission. The courses qualify for credits and are free of charge for participants who are citizens of any EU or EEA country, or Switzerland, or are permanent residents in Sweden. More information can be found at antagning.se. About the course Applied Deep Learning with PyTorch, 5 credits Who is this course for?This course provides the theoretical and practical aspects of deep neural networks. It is intended for students with a background in computer science and engineering. What will you learn from this course?Students will learn about the analysis, design, and programming of deep learning algorithms. The course has two modules: theory and practice. The theoretical content covers basic principles of multi-layer perceptions, spatio-temporal feature extraction with convolutional neural networks (CNNs), and recurrent neural networks (RNNs), classification and regression of big data, and generating novel data samples using generative models. The practical sessions cover the basics of programming with PyTorch. For instance, image classification and semantic segmentation using CNNs, future image frame prediction with RNNs, and image generation with generative adversarial networks. What is the format for this course?Instruction type: Teaching is in English and fully online. It consists of lectures, computer exercises, and project work. In the computer exercises, the student solves small problems using deep learning models. After programming various exercises, the participants will develop an advanced deep learning project. Participants will be encouraged to bring their own data. High-end GPU machines can be provided for the exercises and project.

Explore the different tools and software to design, test, and prototype custom robot parts and robust robot behaviour. In recent years, industries around the world have been getting creative when it comes to incorporating robotics into their workflows. This three-week course offers a fascinating introduction to software and tools currently used in robotics. You’ll build basic knowledge of robotics tools and learn how they can be adapted for different industries. Familiarise yourself with Ubuntu operating system and Gazebo framework Gain hands-on experience using 3D robotics models in simulation Learn from the experts at the cutting edge of control engineering, robotics, and AI This course is designed for anyone interested in using robotic solutions in their role and who wants to learn the basics of robotics frameworks. The course will be given in English.

Maintenance of company equipment, procedures, and budget has always been important to ensuring optimal business performance. However, it has moved on from the trial-and-error approach used in the beginning of the twentieth century. Modern maintenance engineering involves applying engineering principles to optimise company equipment, budget, and procedures. On this three-week course, Luleå University of Technology will introduce the science, management, and other principles you need to be a maintenance technician in the 21st century. Learn maintenance engineering and technology basics Understand and preserve reliability/maintenance balance Study with leading maintenance experts The course will be given in English.

The information and communication technology (ICT) sector is responsible for approx. 1.8-2.8% of the global greenhouse gas (GHG) emissions in 2020, and software is both part of the problems and the solutions. Traditional software engineering principles and techniques do not consider the climate, environment, and sustainability aspects in building and using software for any purpose. We, software engineers, developers, researchers, climate scientists, and various other related stakeholders, need to think about how we can reduce the carbon footprint due to building and using software-intensive systems. Green and sustainable software engineering is an emerging concept that can help reduce the carbon footprint related to software. In this introductory course, we will introduce the concept of green and sustainable software engineering and the engineering process to build green and sustainable software. Topics Sustainable and green computing Sustainable and green software engineering Process Energy efficient computing Sustainability issues in Scientific computing You will learnBy the end of the course, you will be able to: analyze the green and sustainability issues in traditional software engineering, identify and incorporate key elements to be included in the software engineering process to make the software green and sustainable, and use techniques to make your software code energy efficient. Who is the course for?This course is designed for those who are software developers, managers and software related policy makers, or have knowledge about software development, and want to consider the green and sustainability aspects in their everyday life. Also, this course will be useful for computational scientists who build green software and want to know more about these aspects in software engineering. However, this is an introductory course, and it will show a path for life-long learning to build more in-depth knowledge in each concept introduced in this course.