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Lecturer(s)
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Kovařík Filip, Mgr. Ph.D.
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Course content
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The course covers four core thematic areas, in which students progressively explore the principles underlying artificial intelligence, learn to communicate with it effectively, use it as a tool to support their studies, and finally apply it to data analysis, visualisations, and the organisation of their study time. 1. What Is Artificial Intelligence and How Does It Work (Weeks 1-3) The history and development of artificial intelligence; the fundamental principles of how AI functions; types of AI tools and an overview of their range; the capabilities and limitations of AI; ethical questions associated with the use of AI in an academic environment; principles of academic integrity. 2. How to Query AI Effectively (Weeks 4-6) The principle of prompting, the structure of an effective prompt, types of prompts and their uses, iterative refinement of queries, contextual instructions, common mistakes when working with AI, and how to avoid them, and practical exercises with a variety of tools. 3. AI as a Study Aid (Weeks 7-10) AI for supporting writing and text production; summarising and processing lecture content; note-taking and mind mapping; searching for and analysing academic literature using AI; critical verification of information obtained from AI; tools for working with scientific texts. 4. AI for Data, Visualisations, and Study Organisation (Weeks 11-13) Basic data work using AI; generating and editing visual content; creating charts and infographics; AI tools for planning and organising study; task and time management; responsible and reflective integration of AI into everyday academic practice.
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Learning activities and teaching methods
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Monologic Lecture(Interpretation, Training), Dialogic Lecture (Discussion, Dialog, Brainstorming), Work with Text (with Book, Textbook), Demonstration
- Attendace
- 26 hours per semester
- Semestral Work
- 44 hours per semester
- Preparation for the Course Credit
- 20 hours per semester
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Learning outcomes
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The course aims to equip students with the practical competencies needed for meaningful and responsible use of artificial intelligence tools within the context of higher education study. Students will develop an understanding of the principles underlying AI, gain familiarity with the current range of available tools, and learn to use them effectively from formulating precise queries and supporting academic writing to processing literature, working with data, and organising their studies. The module also encompasses a critical reflection on the possibilities and limitations of AI, as well as a conscious grounding of its use in accordance with the principles of academic integrity.
Upon successful completion of the module, students will be able to: - explain the principles underlying the functioning of artificial intelligence tools and place their development within a historical context, - navigate the range of available AI tools, distinguish between their capabilities and limitations, and critically reflect on the ethical questions associated with their use in an academic environment, - apply the principles of effective prompting and formulate precise and purposeful queries for AI tools, - use AI tools to support their studies, including academic writing, note-taking, summarising lectures, and processing scientific texts, - work with tools for searching and analysing academic literature and critically verify information obtained through AI, - integrate AI tools into their everyday studies in a responsible manner and in accordance with the principles of academic integrity.
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Prerequisites
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Basic knowledge of using the internet. No prior knowledge of artificial intelligence is required.
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Assessment methods and criteria
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Student performance, Seminar Work
Regular attendance at seminars and completion of assignments by the specified deadlines. a) Ongoing seminar assignments: students must submit all assigned tasks via MOODLE. Assessment: pass/fail with written feedback; b) Active participation in practical seminars.
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Recommended literature
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Furze, L. (2025). AI ve škole prakticky: Strategie pro využití generativní umělé inteligence ve vzdělávání. Praha.
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Mollick, E. (2024). Co-Intelligence: Living and Working with AI.. New York.
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Phoenix, J., & Taylor, M. (2023). Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs. Sebastopol.
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