FF:CORE100 AI Lab in Practice - Course Information

CORE100 AI Lab in Practice: From Idea to Prototype

Extent and Intensity

2/0/0. 3 credit(s). Type of Completion: k (colloquium).
In-person direct teaching

Teacher(s)

PhDr. Petr Škyřík, Ph.D. (lecturer)
Mgr. Bc. Kateřina Švidrnochová (lecturer)

Guaranteed by

PhDr. Petr Škyřík, Ph.D.
Department of Information and Library Studies – Faculty of Arts
Contact Person: Mgr. Alice Lukavská
Supplier department: Department of Information and Library Studies – Faculty of Arts

Timetable

Wed 12:00–13:40 B2.43, except Mon 17. 11. to Sun 23. 11.

Prerequisites

TYP_STUDIA(BM) && FORMA(P)
The course is primarily intended for students of all faculties of Masaryk University who are interested in the practical use of artificial intelligence in their field of study or professional practice.
Please note: The course is not primarily intended for students of the ISK and DIS study programmes at the Faculty of Arts of MUNI, because in the spring semester there is a course with the same principles called AI in practice.
Prior experience with AI tools is not necessary. The key is:
- interest in experimenting,
- willingness to learn,
- proactive approach,
- willingness to devote time regularly to work on your own project.

Course Enrolment Limitations

The course is offered to students of any study field.
The capacity limit for the course is 40 student(s).
Current registration and enrolment status: enrolled: 34/40, only registered: 2/40, only registered with preference (fields directly associated with the programme): 0/40

Course objectives

The aim of the course is to develop practical skills and design thinking when implementing AI in your own projects across different disciplines. Students will learn to:
- use modern AI tools effectively (especially big language models);
- apply AI in user research, data analysis, prototyping and service personalisation;
- reflect on the ethical and safety aspects of AI,
present and defend their own AI-driven projects.
The course combines theory with practical experiments.
Students can adapt the topic of the project to their academic and professional interests - for example, link it to another course, a term assignment or a bachelor's/master's thesis.

Learning outcomes

Upon successful completion of the course, students will be able to:
- Understand the principles and applications of AI in different contexts and professional domains
Design and prototype AI-enabled solutions from ideation to functional concept -
Effectively use large language models (LLMs) for research, content creation, analysis and data visualization -
Work with vibe coding tools and experiment with multimodal AI systems -
Formulate and debug prompts for different types of tasks.-
Learn the principles and techniques of design thinking and the Double Diamond model for a structured innovation process.
- Apply a human-centred AI approach, i.e. focusing on user needs and responsible use of AI.
- Integrate ethical and safety considerations into the design and use of AI solutions.
- Reflect on own work with AI tools, identify strengths and weaknesses and plan further skills development.
- Present and defend own project, including critical reflection on the benefits and limitations of AI.

Syllabus

• The course will be taught full-time for full-time students, online connection will be possible for distance learning students. The course consists of 12 sessions focusing on the following topics:
• 1. Introduction to the topic, brainstorming projects, design and ethical framing
• 2. Fundamentals of AI, big language models and prompting
• 3. AI in research and information handling
• 4. Data analysis and visualization using AI
• 5. Ideation and vibe coding - creative use of AI in prototyping
• 6. Service personalization and design of AI assistants
• 7. Ethics and safety of AI systems
• 8. AI in user research and idea validation
• 9. Working with multimodal models and generating visual outputs
• 10. Storytelling and presentations supported by AI tools
• 11. Creating final concepts and iterating prototypes
• 12. Preparation of presentation and final reflection Final colloquium with project presentation
• Dates: Wednesday 12:00 - 13:45, room B24, Faculty of Arts, Masaryk University
• Total recommended course time:
• - 21 hours of direct teaching -
• approx. 14 hours of independent experimentation (12 weeks × 60 min)
• - preparation of final presentation and reflection: approx. 5 hours
• - Approximately 40 hours in total.
• Organizational information and links to join will be sent at the beginning of the semester to registered students

Teaching methods

- interactive workshops
- independent and team work on own projects
- expert discussions and peer-learning
- practical testing of tools (LLMs, multimodal models, vibe coding)
- gamified techniques (Tarot Cards of Tech, Ethical Canvas)
- reflection and sharing of experiences

Assessment methods

- Final project (30%) - quality of design, innovation, practical applicability of AI
- Interim challenges (30%) - regular completion of assignments and reflections
- Project presentation (20%) - clear presentation, argumentation and visual design
- Activity (20%) - collaboration, involvement in discussions and reflections on ethical aspects of AI
Participation: - full-time students - mandatory participation in min. 8 meetings
- distance learning students - mandatory participation in min. 10 meetings

Language of instruction

Czech

Study support

https://is.muni.cz/auth/el/phil/podzim2025/CORE100/index.qwarp

Further comments (probably available only in Czech)

Study Materials

Teacher's information

This course is suitable for students of various disciplines and faculties who want to connect AI with their own interests and topics.

In the course, you can work on a project that can be used in another course or as a basis for a bachelor's or master's thesis.

The course emphasizes:

- active experimentation with AI,

- the development of design and critical thinking skills,

- the ability to reflect on your own work with AI, -

the ability to connect technology to human needs and values.

The course is suitable for students who are willing to make an ongoing time investment in experimenting with AI throughout the semester.

• Enrolment Statistics (recent)
  
• Permalink: https://is.muni.cz/course/phil/autumn2025/CORE100