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Course, academic year 2022/2023
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Elements of AI+ - NAIL130
Title: Elements of AI+
Guaranteed by: Department of Software and Computer Science Education (32-KSVI)
Faculty: Faculty of Mathematics and Physics
Actual: from 2022
Semester: both
E-Credits: 3
Hours per week, examination: 1/1, C [HT]
Capacity: unlimited
Min. number of students: unlimited
Virtual mobility / capacity: no
State of the course: taught
Language: Czech, English
Teaching methods: full-time
Additional information:
Note: you can enroll for the course repeatedly
you can enroll for the course in winter and in summer semester
Guarantor: Mgr. Tereza Hannemann, Ph.D.
Mgr. Rudolf Rosa, Ph.D.
Annotation -
Last update: RNDr. Tomáš Holan, Ph.D. (20.05.2022)
AI, artificial intelligence, smart devices, machine learning... We hear these words around us more and more often. From developing new medicines to writing plays to choosing a life partner, AI is gradually making inroads into many areas of human activity. In collaboration with the University of Helsinki, we bring you the online course "Elements of AI", which introduces you to AI without the need to know how to program. Read more:
Aim of the course -
Last update: Mgr. Tereza Hannemann, Ph.D. (29.09.2022)

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

Presentations, seminars, workshops or collaborative reading of articles are designed to deepen the knowledge gained in the online course.

Course completion requirements -
Last update: Mgr. Rudolf Rosa, Ph.D. (14.02.2023)

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:
  • Fill in the link to the certificate and feedback into aform for the Elements of AI+ course, which will be used to further develop and improve the course (the questionnaire is available in Czech and English):

About the online course evaluation: Assessment 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).

We register credits for the course continuously, usually about once a month.

If the duration of the exam period is essential for your studies, from our point of view the dates are governed by the MFF UK academic calendar.

We recommend completing the course at least 14 days before the date by which you wish to receive the credit (among other things, you may have to wait for the peer grading for a while).

The course can be taken only once within studies at the faculty, it is not possible to get credits for it repeatedly. (Not even if you took the course under a different code, such as TVOL0007.)

Literature -
Last update: Mgr. Tereza Hannemann, Ph.D. (20.05.2022)

To the online course:

 Direct link to the online course:

 For more information: or

On artificial intelligence in general:

 Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach (4th Edition). Pearson, 2020.

 Ian Goodfellow and Yoshua Bengio and Aaron Courville. Deep Learning. MIT Press, 2016.

AI in various fields:

 Gundersen, T., & Bærøe, K. (2022). The Future Ethics of Artificial Intelligence in Medicine: Making Sense of Collaborative Models. Science and Engineering Ethics, 28(2), 1-16.

 Schapals, A. K., & Porlezza, C. (2020). Assistance or resistance? Evaluating the intersection of automated journalism and journalistic role conceptions. Media and Communication, 8(3), 16-26.

 Liao, S. M. (Ed.). (2020). Ethics of artificial intelligence. Oxford University Press.

 McCormack, J., Bown, O., Dorin, A., McCabe, J., Monro, G., & Whitelaw, M. (2014). Ten questions concerning generative computer art. Leonardo, 47(2), 135-141.

Teaching methods -
Last update: RNDr. Tomáš Holan, Ph.D. (12.05.2022)

The course will consist of the mandatory online “Elements of AI” course, which is free in Czech and English. The course can be taken and completed independently at the student's own pace.

The course will include lectures, seminars, workshops or collaborative reading of texts. Participation in the face-to-face events is voluntary, and we encourage students who wish to deepen their knowledge of AI beyond the online course to attend.

Syllabus -
Last update: RNDr. Tomáš Holan, Ph.D. (12.05.2022)

Element of AI is an open online course with 6 thematic chapters:

1. What is Artificial Intelligence?

2. Problem solving using Artificial Intelligence

3. Artificial intelligence in the real world

4. Machine learning

5. Neural networks

6. 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.

The Elements of AI+ course also offers the opportunity to voluntarily attend lectures, seminars, workshops or collaborative reading of texts focusing on artificial intelligence. These "events" will extend the online course with additional knowledge, especially the workshops will be conducted to give students and instructors a chance to meet.

A list of "events" for the current semester will be continuously published here:


Course guarantors: Tereza Hannemann and Rudolf Rosa from Matfyz are available to help all students at: Questions concerning the "operation" of the course, i.e. technical and administrative matters, as well as questions that are directed at the content of the online course itself can be directed here.

Medical students can contact Peter Kajzar from the 1st Faculty of Medicine with questions about the content of the online course.

Students of theological faculties can contact František Štěch of the Protestant -Theological Faculty with questions about the content of the online course.

Students of the Faculty of Arts can contact Nikol Kopáňková from the Department of Psychology with questions about the content of the online course.

Students of the Faculty of Social Sciences can contact Veronika Mackova from the Department of Journalism (Institute of Communication Studies and Journalism) with questions about the content of the online course.

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