Course: BIP on Artificial Intelligence for Students

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Course title BIP on Artificial Intelligence for Students
Course code KFA/BIP1
Organizational form of instruction Lecture + On-line Activities
Level of course Bachelor
Year of study not specified
Semester Winter and summer
Number of ECTS credits 3
Language of instruction English
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Course availability The course is available to visiting students
Lecturer(s)
  • Laštovička Ondřej, Mgr. Ph.D.
  • Dvořáček Martin, Mgr.
Course content
Synchronous online lecture 1: Introduction; ethics and morality of AI Synchronous online lecture 2: Concept and context of AI, history and trends Block 1: Generative AI fundamentals and prompting, generative AI for personal organization and communication Block 2: Generative AI for support personal learning Block 3: Generative AI for creating learning supportive imaging, presentations and learning materials Block 4: Generative AI for support in research Block 5: Generative AI for Clinical Practice; Colloquium

Learning activities and teaching methods
Lecture, Demonstration
  • Attendace - 36 hours per semester
  • Attendace - 4 hours per semester
  • Homework for Teaching - 25 hours per semester
  • Semestral Work - 10 hours per semester
Learning outcomes
The aim of this course is to introduce physiotherapy students to the world of artificial intelligence (AI) and its practical applications in their field. The course focuses on developing skills in using AI to streamline the study process, enhance personal productivity, and support the creation of scientific work. Emphasis is also placed on the ethical aspects of using AI.
The course is intended for physiotherapy students.
Prerequisites
Basic computer literacy, basic knowledge of English terminology. The student should have their own laptop or tablet.

Assessment methods and criteria
unspecified
Active participation in class, completion of assigned tasks.
Recommended literature


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