Artificial intelligence enriches every area of life
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In the exciting world of artificial intelligence, you will learn to programme computers so that they can make independent decisions and perform tasks that are normally done by humans. As a student on the Artificial Intelligence degree programme you will acquire the specialist knowledge required to build AI systems. In the beginning, the programme covers basic topics such as mathematics, programming, algorithms and data structures, operating systems, networks and databases. As you progress, you will explore complex AI topics such as machine learning, computer vision, natural language processing, big data, deep learning, autonomous robotics and computational logic.
In the sixth and seventh semesters, you can customise your studies by taking elective courses that match your interests and personal focus, such as healthcare, mobility, energy management, production, shared-cost services/providers or gaming. After successfully completing your studies, you will be able to use AI solutions to solve problems in specialist departments. AI also enables better management of limited resources, strengthening the balance between economic and ecological sustainability.
Fact Sheet Artificial Intelligence
Degree: Bachelor of Science (B.Sc.)
Duration: 7 semesters (3.5 years)
ECTS points: 210
Start: October (winter semester)
Study Location: Deggendorf
Language of instruction: German (see language requirements)
Application period: 15 April - 15 July
Admission requirements:
- General German university entrance qualification, or please check your eligibilty at the DAAD if you own an international qualification
- If English is not your native language, proof of sufficient English skills is necessary
Prerequisites: Knowledge of basic STEM subjects is an advantage
Advanced degree programmes:
- Master Artificial Intelligence and Data Science
- Master Applied Computer Science
- Master of Applied Research
- Master Business Informatics
Fees:
- €72 student union fee per semester
- * International applicants and students
- IT scholarship: Funding for prospective IT talents
Contact:
- nformation on programme content: ain-b-info@th-deg.de
- General information about studying at DIT: Study orientation
- General info on studying at DIT: prospective student advisors
- Information for freshers
We also offer the degree programme in English: B.Sc. Artificial Intelligence
Download: Course flyer
Career Prospects
Almost every industry needs automated decision-making by means of AI in order to remain competitive. Examples of artificial intelligence applications include automated driving, smart homes, facial recognition, music streaming, medical image processing and diagnostics, predictive maintenance, navigation, robotics and digital voice assistants. You will be able to work in all of these areas. As a graduate, you will be able to analyse data, develop AI systems, manage AI projects, advise managers and clients on these topics and conduct research in the field of AI. With extensive ongoing investment in AI by companies and governments, there are many job opportunities for you, such as:
- Data scientist
- AI engineer
- Software engineer
- Consultant
- Business developer
- Project manager
- Researcher
There are potential employers for graduates of this degree programme in all sectors, particularly in the software industry. However, another option for you is to start your own business after graduating.
Subject Overview
Overview of lectures and courses, SWS (Semesterwochenstunden = weekly hours/semester) and ECTS (European Credit Transfer and Accumulation System) in the Bachelor's degree Artificial Intelligence.
| 1. Semester | SWS | ECTS |
| Mathematics 1 | 4 | 5 |
| Programming 1 | 4 | 5 |
| Basics of Informatics | 4 | 5 |
| Operating Systems and Networks | 4 | 5 |
| Introduction to Artificial Intelligence | 4 | 5 |
| Key Qualifications I (Media Skills and Self Organisiation, Business Administration) | 4 | 5 |
| 2. Semester | SWS | ECTS |
| Mathematics 2 | 4 | 5 |
| Programming 2 | 4 | 5 |
| Algorithms and Data Structures | 4 | 5 |
| Internet Technologies | 4 | 5 |
| Computational Logic | 4 | 5 |
| Key Qualifications 2 (Technical Language) | 4 | 5 |
| 3. Semester | SWS | ECTS |
| Data Bases | 4 | 5 |
| Stochastics | 4 | 5 |
| Project Management | 4 | 5 |
| Assistance Systems | 4 | 5 |
| AI-Programming | 4 | 5 |
| Key Qualifications 3 (Technology Ethics and Sustainability, Academic Work) | 4 | 5 |
| 4. Semester | SWS | ECTS |
| Language Processing | 4 | 5 |
| Human Factors and Human-Machine Interaction | 4 | 5 |
| Machine Learning | 4 | 5 |
| Image Comprehension | 4 | 5 |
| Software Engineering | 4 | 5 |
| Key Qualifications 4 (Compliance, Data Protection and IT Law) | 4 | 5 |
| 5. Semester | SWS | ECTS |
| Practice Module (Industrial Placement, Practice Seminar, Practice Accompanying Course) | ||
| 6. Semester | SWS | ECTS |
| Seminar Current Developments in AI | 4 | 5 |
| Autonomous Robotics | 4 | 5 |
| AI-Project | 4 | 5 |
| Deep Learning/Big Data | 4 | 5 |
| Compulsory Elective Module 1 | 4 | 5 |
| Key Qualifications 5 (Team Development and Intercultural Communication, Business Formation) | 4 | 5 |
| 7. Semester | SWS | ECTS |
| Compulsory Elective Module 2 | 4 | 5 |
| Compulsory Elective Module 3 | 4 | 5 |
| Compulsory Elective Module 4 | 4 | 5 |
| Bachelor Module (Bachelor Thesis, Bachelor Seminar) | 2 | 15 |