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Introduction to the Basics of Artificial Intelligence

Module name (EN):
Name of module in study programme. It should be precise and clear.
Introduction to the Basics of Artificial Intelligence
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Applied Informatics, Bachelor, SO 01.10.2026
Module code: PIB-GKI
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P221-0213
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
2V+2S (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
5
Semester: 5
Mandatory course: no
Language of instruction:
German
Assessment:
Written exam, Duration 90 min.

[updated 05.11.2025]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

KIB-GKI (P221-0213) Computer Science and Communication Systems, Bachelor, ASPO 01.10.2022 , semester 5, optional course
PIB-GKI (P221-0213) Applied Informatics, Bachelor, ASPO 01.10.2022 , semester 5, optional course
PIB-GKI (P221-0213) Applied Informatics, Bachelor, SO 01.10.2026 , semester 5, optional course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 150 hours (equivalent to 5 ECTS credits).
There are therefore 105 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Christoph Tholen
Lecturer: Prof. Dr. Christoph Tholen

[updated 25.09.2025]
Learning outcomes:
After successfully completing this module, students will be able to name and distinguish between different subfields of artificial intelligence. They will understand the most important principles and be able to independently implement simple tasks from various subfields. Students will be able to identify suitable artificial intelligence methods and procedures and apply them in simple application scenarios. They will work independently on simple AI systems in small teams. Students will discuss ethical issues associated with the use of AI in detail and take these into account when designing AI systems.

[updated 05.11.2025]
Module content:
Historical development of artificial intelligence
Propositional logic
First-order predicate logic
Expert systems
Fuzzy logic
Uninformed and informed searches, heuristics
Supervised and unsupervised machine learning


[updated 05.11.2025]
Teaching methods/Media:
Slides, programming exercises in PROLOG, Python, and KNIME

[updated 05.11.2025]
Recommended or required reading:
Ertel, W.: Grundkurs Künstliche Intelligenz: Eine praxisorientierte Einführung. Springer Fachmedien, Wiesbaden (2021). https://doi.org/10.1007/978-3-658-32075-1
Frochte, J.: Maschinelles Lernen: Grundlagen und Algorithmen in Python. Hanser, München (2019). https://doi.org/10.3139/9783446459977.
Russell, S.J., Norvig, P.: Künstliche Intelligenz: ein moderner Ansatz. Pearson, München, Germany (2012).
Karatas, M.: Eigene KI-Anwendungen programmieren. Rheinwerk Verlag, Bonn (2024). ISBN 978-3-8362-9763-9
Hopgood, A.A.: Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence. CRC Press, Boca Raton (2021). https://doi.org/10.1201/9781003226277.


[updated 05.11.2025]
 
[Thu Nov 20 05:52:23 CET 2025, CKEY=peidgdk, BKEY=pi3, CID=PIB-GKI, LANGUAGE=en, DATE=20.11.2025]