Course: Elements of AI

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Course title Elements of AI
Course code KEMA/X1104
Organizational form of instruction no contact
Level of course Bachelor
Year of study not specified
Semester Winter and summer
Number of ECTS credits 3
Language of instruction Czech, English
Status of course Compulsory-optional
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)
  • Siviček Tomáš, Ing. PhD.
Course content
Element of AI is an open online course with 6 thematic chapters: - what is Artificial Intelligence? - problem solving using Artificial Intelligence - artificial intelligence in the real world - machine learning - neural networks - implications Each of the chapters contains text and interactive elements that are designed to support learning. The online course format will give students the opportunity to schedule the work at their own pace and time. The time commitment to complete the online course ranges from 20-50 hours, depending on prior knowledge of the topic and learning approach.

Learning activities and teaching methods
unspecified, unspecified
Learning outcomes
After successfully completing the course the student will be able to understand: - what is autonomy and adaptability in the context of artificial intelligence - how the Turing test works - how to formulate a real-world problem in a form that is searchable - what is a neural network - what technical methods form the basis for neural networks - how challenging it is to predict the future - what are the main societal impacts of AI, including algorithmic bias, AI-generated content

Prerequisites
unspecified

Assessment methods and criteria
unspecified
To successfully complete a course for which a student receives 3 credits, the following is required: - successfully complete the online course "Elements of AI" in Czech or English at: https://course.elementsofai.com - complete the Elements of AI course form, including a link to the certificate at: https://forms.gle/An5fc7xJ4hzmQrQ97 Assessment of course is based on exercises, including multiple choice quizzes, numerical exercises, and questions that require a written answer. The multiple choice and numerical exercises are automatically checked, and the exercises with written answers are reviewed by other students (peer grading) and in some cases by the instructors. Successful completion of the course requires at least 90% completed exercises and minimum 50% correctness. The course is graded as pass/fail (no numerical grades).
Recommended literature


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