Artificial Intelligence

With the advances of modern technology, cybersecurity has become hard to provide and guarantee. AI can enhance cybersecurity, but also undermine it. In this course, you will learn the different uses of AI for defending and attacking a cybersystem, from fingerprint recognition for authenticating legitimate users, to fuzzing attacks for crashing vulnerable targets.

As AI systems become more common and expand their abilities, the decisions they made have a crucial impact on society as a whole. Whether they are designed to recommend content or product online, to assist judges or physicians in their decision-making, or to decide how to distribute mortgages or video surveillance cameras, these systems can have a crucial and lasting impact on all of us. For this reason, it is of paramount importance that those in charge of designing such systems work toward ethical and responsible systems. This course covers the theoretical and practical aspects of normative ethics and how they apply to AI systems, discuss how AI systems can become biased, as well as how to prevent and correct possible bias.  Through concrete examples, case studies, and project, this course aims at raising awareness on the problem of ethical AI as well as giving the students practical experience on how to ensure ethical and responsible development of AI systems in their everyday work. This course is given on-line with three mandatory Zoom-meetings. This course is directed towards working professionals.

The promise of intelligent robot systems is that they can accomplish more tasks, more efficiently than a single-purpose industrial robotic solution. Intelligent robots act competently because they can plan, sequence and enact the actions that are appropriate in the context in which they find themselves. In order to achieve this capability, intelligent robots use Artificial Intelligence (AI) Search Methods. These are general-purpose algorithms for solving combinatorial problems, in other words, they constitute a robot's "reasoning engine". This course introduces students to the most important types of AI search methods. These are then instantiated in three industrially-relevant application contexts, namely, resource scheduling, motion planning, and multi-robot coordination.

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.

ROS (Robot Operating System) is a common set of tools used in academia to do research within autonomous systems. It shortly provides a middleware for handling communication, as well as interfacing sensors and actuators, visualization, simulation and datalogging and infrastructure where it is easy to share your own methods and algorithms. The latter has allowed a large set of different of state-of-the-art research approaches to be readily available for downloading. Due to its popularity it is also getting more widespread in the industrial community, especially in R&D. This course will give you hands-on experience how to utilize these tools and apply them to a problem of your choice.

Today's ever-growing AI technology offers many different business opportunities. However, starting an AI project and maximizing the balance between business impact and resources is still a challenging task, requiring a thorough understanding of what AI can and cannot do for your business. This free course will give you an introduction to: What you can use artificial intelligence for How you as a business leader should approach AI from a business strategy perspective What key strategic decisions you need to make upfront What skills you need to succeed How you should start and proceed with different steps of your project The course was developed in collaboration with EIT Digital. See all free online courses that KTH offers

Today's ever-growing AI technology offers many different business opportunities. However, starting an AI project and maximizing the balance between business impact and resources is still a challenging task, requiring a thorough understanding of what AI can and cannot do for your business. This free course will give you an introduction to: What you can use artificial intelligence for How you as a business leader should approach AI from a business strategy perspective What key strategic decisions you need to make upfront What skills you need to succeed How you should start and proceed with different steps of your project The course was developed in collaboration with EIT Digital. See all free online courses that KTH offers

Discover the basics of computer vision and its role in Industry 4.0.Humans are in the midst of what is referred to as the Fourth Industrial Revolution, or Industry 4.0: the advent of new technologies that will forever change the face of business, and chief among them is computer vision. This three-week course from the Luleå University of Technology will give you a solid introduction to computer vision and help you explore its effects on industry and business. Once you complete the course, you’ll understand the potential applications of computer vision and be empowered to shape its future. This course will guide you through this journey to have a better understanding of the techniques that stand behind this field, and how you can get the benefit of using CV in your current business. The course will cover he concepts of the following fields, image processing, machine learning, deep learning, and use cases of computer Vision in business. Anyone in industry and academia who wants to boost their digital skills and gain confidence in how computer vision practices have evolved and might add a noticeable positive impact to their business and careers. This may include:  Employees, Executives, Directors, Senior Managers, Founders, and Entrepreneurs  Undergraduates and post-graduates  Researchers, teachers from majors related to business This course will be given in English.

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 Critical design and practical ethics for AI, 3 credits Who is this course for? Artificial Intelligence (AI) is being increasingly implemented and used in society today. It has already proven to have an impact on the individual, organization and society, and this impact will most likely only increase. Therefore, it is important to understand the ethical issues that may arise from use of AI, as well as to adopt a critical stance to the technology’s impact. The course introduces critical and ethical issues surrounding data and society, to train the student to problematize and reason about artificial intelligence (AI). You are most likely a designer, innovator, or product manager that works with digital services and products. What will you learn from this course? The course deals with different perspectives on AI and its real and potential effect on organizations and society. The course is based on five different perspectives on AI: accountability, surveillance capitalism, power and bias, sustainability, and trust. The course material consists of recent and relevant literature on the impact of, and critical perspectives on AI. Active discussions founded in different ethical perspectives are also an important part of the course. What is the format of this course? This course is primarily self-paced, with a few synchronous meetings. Most activities are based on the student’s having consumed specified material beforehand, such as video lectures, podcasts, articles, and books. Active discussions, both in online forums and during synchronous meetings, are an important part of the course.

The Internet of Things (IoT) is a networking paradigm which enables different devices (from thermostats to autonomous vehicles) to collect valuable information and exchange it with other devices using different communications protocols over the Internet. This technology allows to analyse and correlate heterogeneous sources of information, extract valuable insights, and enable better decision processes. Although the IoT has the potential to revolutionise a variety of industries, such as healthcare, agriculture, transportation, and manufacturing, IoT devices also introduce new cybersecurity risks and challenges. In this course, the students will obtain an in-depth understanding of the Internet of Things (IoT) and the associated cybersecurity challenges. The course covers the fundamentals of IoT and its applications, the communication protocols used in IoT systems, the cybersecurity threats to IoT, and the countermeasures that can be deployed. The course is split in four main modules, described as follows: Understand and illustrate the basic concepts of the IoT paradigm and its applications Discern benefits and drawback of the most common IoT communication protocols Identify the cybersecurity threats associated with IoT systems Know and select the appropriate cybersecurity countermeasures Course Plan Module 1: Introduction to IoT Definition and characteristics of IoT IoT architecture and components Applications of IoT Module 2: Communication Protocols for IoT Overview of communication protocols used in IoT MQTT, CoAP, and HTTP protocols Advantages and disadvantages of each protocol Module 3: Security Threats to IoT Overview of cybersecurity threats associated with IoT Understanding the risks associated with IoT Malware, DDoS, and phishing attacks Specific vulnerabilities in IoT devices and networks Module 4: Securing IoT Devices and Networks Overview of security measures for IoT systems Network segmentation, access control, and encryption Best practices for securing IoT devices and networks Organisation and Examination Study hours: 80 hours distributed over 7 weeks Scehduled online seminars:  January 30th 2024, February 12th 2024 and 11th of March Examination, one of the following: Analysis and presentation of relevant manuscripts in the literature Bring your own problem (BYOP) and solution. For example, analyse the cybersecurity of the IoT network of your company and propose improvements The number of participants in the course is limited, so please hurry with your application!

The course consists of three parts that introduce and explore the design of extended realities along different axes: a framing perspective, illustrating what XR is, how it has evolved, and how designing XR differs from traditional digital design practices; a methodological perspective, detailing those XR-specific theory and methods that address XR design issues; and a practical perspective, exploring best practices and concrete design activities through direct application of these to a case. Each part consists of lectures, readings, supervision, and an assignment centered on the specific topics discussed in the part of the course.Assignments are carried out by students individually and will be peer-reviewed first and then discussed with the teachers and the class using a design critique approach.

KursinnehållKursen syftar till att ge en introduktion och överblick av artificiell intelligens. Fokus ligger på att förstå begreppet och några viktiga tekniker som hur sökning och maskininlärning fungerar samt konsekvenser av AI på samhället.  Börja läsa när du vill Du kan börja läsa kursen i stort sett när du vill då kursen är en online-kurs med flexibel antagning. Du gör ansökan till den termin du tänker börja läsa kursen. Vill du börja direkt så ansöker du till innevarande termin, eller så väljer du den termin du tänker börja. Termin väljer du här ovan, så kommer du till rätt ansökningstillfälle. KursformatKursen är en distanskurs som görs i egen takt och hanteras i sin helhet i en web-baserad kursmiljö. Kursen baseras på självstudier av kursmaterialet och examineras med självrättande tester och inlämningar. Du som har gjort Elements of AI kan anmäla dig till den här kursen för att få dina resultat validerade. Det gäller både den svenska och den engelska versionen av kursen. Du måste inte göra om kursen, däremot måste du ladda upp certifikatet från Elements of AI och göra ett valideringstest med frågor motsvarande de som finns i Elements of AI för att säkerställa att det verkligen är du som gått igenom kursen. För mer information se denna länk. Kursen handleds över internet. Information om behörighetObservera att du vid ansökan till kursen måste kunna styrka att du har grundläggande behörighet. Om dina gymnasiemeriter inte redan finns på dina sidor på antagning.se så behöver du ladda upp gymnasieexamen, eller motsvarande, på antagning.se i samband med din ansökan.