About the studyprogram
Research-oriented
Students who study Artificial Intelligence Engineering 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.
Hard- and Softwaresystems
Integrate algorithms into hardware and software systems while exploring application areas 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 and electrical engineering fundamentals to efficiently implement artificial intelligence applications.
This IT study program teaches you the fundamentals of computer science, electrical engineering and psychology to develop complex hardware / software-based systems using or for use in AI. After your studies, you can specialize in one of our IT master's programs (especially AI technology) or start your career directly.
Inform yourself and decide for
your AI Engineering 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
Wintersemester 2024/2025 (version from 21.11.2024)
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.
| Zeit | Mo | Di | Mi | Do | Fr |
|---|---|---|---|---|---|
|
1. Block 07.30-09.00 |
|
|
UE - Grundlagen der Elektrotechnik
(LG3A/352)
UE - Elektrotechnik I: Gleichstromtechnik und Felder
(LG3A/352) |
|
|
|
2. Block 09.15-10.45 |
PS - Methoden und Technologie der Künstlichen Intelligenz
(ZHG/SR2) |
UE - Grundlagen der Elektrotechnik
(LG3A/352)
UE - Elektrotechnik I: Gleichstromtechnik und Felder
(LG3A/352) |
UE - Mathematik IT-1 (Diskrete Mathematik)
(HG0.17) |
UE - Mathematik IT-1 (Diskrete Mathematik)
(HG0.17) |
VL - Entwicklung von Softwaresystemen
(ZHG/HSC) |
|
3. Block 11.30-13.00 |
PR - Programmierpraktikum
(VG1C/0.03) |
VL - Entwicklung von Softwaresystemen
(ZHG/HSC) |
PR - Programmierpraktikum
(VG1C/0.03) |
PR - Programmierpraktikum
(VG1C/0.03) |
VL - Programmierpraktikum
(ZHG/HSC) |
|
4. Block 13.45-15.15 |
VL - Mathematik IT-1 (Diskrete Mathematik)
(ZHG/Audimax1) |
VL - Mathematik IT-1 (Diskrete Mathematik)
(LG1A/HS2) |
UE - Mathematik IT-1 (Diskrete Mathematik)
(LG1A/304) |
|
PR - Programmierpraktikum
(VG1C/0.03) |
|
5. Block 15.30-17.00 |
UE - Entwicklung von Softwaresystemen
(ZHG/SR1) |
UE - Entwicklung von Softwaresystemen
(HG0.19)
TU - Mathematik IT-1 (Diskrete Mathematik)
(ZHG/HSB) |
|
|
|
|
6. Block 17.30-19.00 |
UE - Entwicklung von Softwaresystemen
(ZHG/SR1) |
UE - Entwicklung von Softwaresystemen
(HG0.18) |
|
|
|
The information in the timetable is subject to change without notice!
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:
- 1 lecture every week (2 semester hours = 2 × 45 min)
- 1 seminar every week (2 semester hours = 2 × 45 min)
- 1 exercise every week (2 semester hours = 2 × 45 min)
Exam requirements:
No prerequisite is required. However, experience shows that the exercise should be attended if you want to pass the exam.
Further information:
The module deals with physical and electrical engineering backgrounds that contribute to the understanding of technical computer science. Transistors, electromagnetic fields and circuits are discussed.
To the official course description →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
Wintersemester 2024/2025 (version from 21.11.2024)
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.
11112: Mathematik IT-1 (Diskrete Mathematik) →
11213: Mathematik IT-3 (Analysis) →
11744: Kognitive Systeme: Perzeption und Aktion →
11908: Systemtheorie I →
12102: Programmierpraktikum →
12104: Entwicklung von Softwaresystemen →
12330: Datenbanken →
12696: Grundlagen der Elektrotechnik →
13567: Methoden und Technologie der Künstlichen Intelligenz →
11113: Mathematik IT-2 (Lineare Algebra) →
11909: Systemtheorie II →
11911: Grundzüge der Kognition und Wahrnehmung →
11926: Statistik für Anwender →
12101: Algorithmieren und Programmieren →
12697: Wechselstromtechnik →
13564: Ethik, Gesellschaft, Medien →
11352: Informations- und Kodierungstheorie →
11865: Allgemeine Physik I (Mechanik, Thermodynamik) →
11867: Allgemeine Physik III (Optik, Atome und Moleküle) →
12838: Analogtechnik →
33306: Nachrichtenübertragung →
33315: Analoge Schaltungen →
11388: Audio- und Signalverarbeitung →
11868: Allgemeine Physik IV (Festkörperphysik) →
11901: Mobile Kommunikationssysteme →
11903: Digitaltechnik →
12214: Digitaltechnik-Praktikum →
12352: Mikroelektronik: Entwurfsautomatisierung für digitale Schaltungen →
12697: Wechselstromtechnik →
13841: Speech Processing →
33305: Nachrichtensysteme →
33320: Digitale und Mixed-Signal-Schaltungen →
11454: Grundlagen der Rechnernetze →
11787: Theoretische Informatik →
11861: Operating Systems II (Multi-Level Memory Management) →
11881: Foundations of Data Mining →
12202: Softwarepraktikum →
12317: Technische Informatik (Seminar Computer Engineering) →
12339: Betriebssysteme II (Speicherverwaltung: Mechanismen und Strategien) →
12351: Grundlagen des Data Mining →
13565: Einführung in Maschinelles Lernen →
13566: Praktikum Maschinelles Lernen →
11293: Modellierung, Bearbeitung und Visualisierung von 3D-Objekten →
11415: Graphentheorie →
11450: Effiziente Algorithmen →
12204: Betriebssysteme I →
12329: Approximationsalgorithmen →
12341: Verteilte und Parallele Systeme I (Grundlagen) →
12342: Praktikum Verteilte und Parallele Systeme →
12350: Compilerbau →
13838: Information Retrieval →
14012: Angewandte Modellierung und Systemsimulation →
The provided Modules and Associations are subject to change without notice and may not be complete!