Course: Elements of AI

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Course title Elements of AI
Course code KUMK/ELAI
Organizational form of instruction Lesson
Level of course Master
Year of study not specified
Semester Summer
Number of ECTS credits 2
Language of instruction Czech
Status of course unspecified
Form of instruction eLearning
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Šula Tomáš, PhDr. PhD.
Course content
The Elements of AI project is a series of free online courses developed by MinnaLearn and the University of Helsinki. We want to motivate as many people as possible to learn about AI and understand what it can and cannot achieve. In addition, participants in this course, which combines theory with practical tasks, will learn how they can start creating AI-based methods. The course can be completed at your own pace.

Learning activities and teaching methods
unspecified
prerequisite
Knowledge
Prerequisities are not set
Prerequisities are not set
Skills
Prerequisities are not set
Prerequisities are not set
learning outcomes
Knowledge
Define what AI is.
Define what AI is.
Explain how AI can be used to solve problems.
Explain how AI can be used to solve problems.
Describe how AI is used in the real world.
Describe how AI is used in the real world.
Identify the difference between AI and machine learning or explain their relationship.
Identify the difference between AI and machine learning or explain their relationship.
List the possible implications of using AI.
List the possible implications of using AI.
Skills
Use basic AI tools.
Use basic AI tools.
Propose the use of AI in solving problems within the field.
Propose the use of AI in solving problems within the field.
Determine possible approaches to applying AI in practice.
Determine possible approaches to applying AI in practice.
Identify the applicability of AI.
Identify the applicability of AI.
Use AI within an ethical framework.
Use AI within an ethical framework.
teaching methods
Knowledge
E-learning
E-learning
Skills
E-learning
E-learning
assessment methods
Knowledge
Written examination
Written examination
Recommended literature


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