COURSE DESCRIPTION
The aim of the course is to introduce the participants into methods and tools for verifying systems that need to react to external stimuli. The methods use system models with precise formal semantics and will span model-checking as well as deductive verification.
A set of simple examples as well as real-world applications will be used throughout the course to illustrate the methods and their tool support. The objective of the course is to understand the underpinning theories of formal verification, and learn how to apply tool support in order to verify system models.
This course provides an understanding of automating software testing using program analysis with the goal of intelligently and algorithmically creating tests. The course covers search-based test generation, combinatorial and random testing while highlighting the challenges associated with the use of automatic test generation. You will learn: Understand algorithmic test generation techniques and their use in developer testing and continuous integration. Understand how to automatically generate test cases with assertions. Have a working knowledge and experience in static and dynamic generation of tests. Have an overview knowledge in search-based testing and the use of machine learning for test generation.
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.
Målet med kursen är att ge lärare fortbildning inom ämnet djurvälfärd och hållbarhet. Kursens mål är också att ge lärare inspiration att designa sin egen undervisning, att ge lärare möjlighet att ta till sig ny forskning och att dela med sig av läraktiviteter som kan användas av fler.
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.
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!