About the studyprogram
Research-oriented
Students who study Artificial Intelligence at the BTU Cottbus-Senftenberg benefit from an bachelor degree based on recognized scientific standards.
Professional Qualifying
A university bachelor degree provides you with all the foundations required to start a professional career in the area of IT and continue educating yourself on your own.
Bachelor-Thesis
Your first scientific work that you create under supervision. You work on various topics and develop a prototype.
Algorithmen und Methoden
Algorithms and methods are the basis for the development of intelligent systems and therefore a necessity for the subject of AI.
Ethical Concerns
Prevent the world from being taken over by robots and discuss what place AI should have in everyday life.
Theoretical Knowledge
Learn the key mathematical principles to understand how Artificial Intelligence works.
This IT study program teaches you the fundamentals of computer science, psychology and mathematics to understand and further develop AI methods. After your studies you can specialize in one of our IT master's programs (especially Artificial Intelligence) or start your career directly.
Inform yourself and decide for
your AI studies at BTU
We provide all the important information about the study program and the start of studies for your decision-making process.
First semester schedule
Sommersemester 2024 (version from 12.04.2024)
To make our first semester more successful, we offer you the possibility to view your schedule directly. In future semesters, you will have more freedom and need a personalized schedule.
Events:
- 2 lectures every week (4 semester hours = 4 × 45 min)
- 1 exercise every week (2 semester hours = 2 × 45 min)
Exam requirements:
Submission of a group exercise sheet every week (at least 75% solved correctly; on request with revision)
Further information:
This module leads you to the practice of software development. This includes the analysis, the design, the implementation and the testing of software. For further information, see the module description.
To the official course description →Events:
- Depending on the selected module
Exam requirements:
Depending on the selected module
Further information:
When choosing FÜS, you choose a module that is not IT-related. For this, there is a FÜS catalog with all modules, as well as a list of modules that may not be chosen.
To the FÜS list →Events:
- 2 lectures every week (4 semester hours = 4 × 45 min)
- 1 exercise every week (2 semester hours = 2 × 45 min)
- 1 optional Tutoring of the FSR IT every week (2 semester hours = 2 × 45 min)
Exam requirements:
Submission of an exercise sheet every week (at least 50% solved correctly), as well as participation in the mock exam
Further information:
The module deals with the mathematical-logical foundations that you need in the study of computer science. This includes formal logic, combinatorics, the Landau notation and later an introduction to graph theory.
To the official course description →Events:
- 1 Proseminar every week (2 semester hours = 2 × 45 min)
Exam requirements:
Currently unknown
Further information:
Currently unknown
To the official course description →Events:
- 1 lecture every second week (1 semester hour = 1 × 45 min)
- 1 practical exercise every week (2 semester hours = 2 × 45 min)
Exam requirements:
Weekly submission of exercise sheets (70%) and participation in a programming test (30%). In total, 75% of the points must be reached to pass the module.
Further information:
The course introduces the programming language Java. The lectures provide additional background and information that are helpful for the practical exercises.
To the official course description →Current modules in semester
Sommersemester 2024 (version from 12.04.2024)
Here you can find all modules and categories offered in this semester. Use our Timetable Creator → to create your individual timetable. If you have questions about the module selection, please contact the FSR or the academic advisor.
13862: Optimierung und Operations Research →
13863: Mathematical Statistics →
11322: Optimierungsmethoden des Operations Research →
11331: Mathematische Statistik →
11333: Optimierung II →
11409: Kombinatorik →
11942: Numerische Mathematik →
13565: Einführung in Maschinelles Lernen →
13566: Praktikum Maschinelles Lernen →
11909: Systemtheorie II →
12101: Algorithmieren und Programmieren →
12317: Fortgeschrittene Methoden der Softwaretechnik →
12350: Compilerbau →
13564: Ethik, Gesellschaft, Medien →
14012: Angewandte Modellierung und Systemsimulation →
11293: Modellierung, Bearbeitung und Visualisierung von 3D-Objekten →
11374: Einführung in die Künstliche Intelligenz →
11450: Effiziente Algorithmen →
11692: Medien- und Kultursemiotik →
11764: Modellierung biologischer Systeme →
11787: Theoretische Informatik →
11908: Systemtheorie I →
12102: Programmierpraktikum →
12104: Entwicklung von Softwaresystemen →
12202: Softwarepraktikum →
12311: Grundzüge der Computergrafik →
12329: Approximationsalgorithmen →
12349: Moderne Funktionale Programmierung →
12696: Grundlagen der Elektrotechnik →
The provided Modules and Associations are subject to change without notice and may not be complete!