Course: Artificial Intelligence: Modern applications, security, and trustworthiness

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Course title Artificial Intelligence: Modern applications, security, and trustworthiness
Course code FAI/AEXUI
Organizational form of instruction Lecture
Level of course unspecified
Year of study not specified
Semester Winter and summer
Number of ECTS credits 3
Language of instruction Czech
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Šenkeřík Roman, prof. Ing. Ph.D.
Course content
This Blended Intensive Programme (BIP) equips students (and early-career/full professionals) with up-to-date knowledge and practical skills to design, deploy, and govern AI responsibly across education, industry, and public services. The 5-day structure blends 2.5 days of expert talks and dialogues with 2.5 days of lectures, guided labs, and hands-on workshops. Concretely, expert-led content spans invited talks and panels on cross-cultural collaboration in AI, ethics and disinformation, AI avatars in education, explainability and AI in healthcare, and university?industry co-creation. The practice-oriented track covers: a training day on secure and responsible AI use, workshop afternoons with a deep dive on ?Generative AI for Automatic Program Discovery,? where participants will see our EASE framework (Effortless Algorithmic Solution Evolution) in action for orchestrated, feedback-driven algorithm design. And a last day focused on modern cybersecurity and AI-for-cybersecurity. The BIP?s overarching objectives are to: (1) align AI education with real-world needs, also thanks to PIONEER-alliance collaborations, (2) foster critical and ethical AI literacy, and (3) develop portable competencies through mini-projects and demonstrations that transfer back to students' and professionals? home institutions and communities.

Learning activities and teaching methods
unspecified
Recommended literature


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester