of all dit graduates
will find a job
within 2 months
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#naturallanguageprocessing #deeplearning #bigdata #industry4.0 #autonomousdriving #robotics #medicalimaging #languageprocessing #generativeAI
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 all-English 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. This English-language bachelor's degree programme also provides excellent preparation for an international working environment.
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.
Degree: Bachelor of Science (B.Sc.)
Duration: 7 semesters (3.5 years)
ECTS points: 210
Start: October (winter semester)
Study Location: Deggendorf
Taught in: English
Application period: 15/04-15/06
Course specialities:
Admission requirements:
Prerequisites: Knowledge of basic STEM subjects is an advantage
Application procedure: Read step by step of how to apply
Postgraduate opportunities:
Fees:
Download: Degree programme flyer
Contact:
We also offer the degree programme in German: B.Sc. Künstliche Intelligenz
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:
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.
Admission is a combination of the required university entrance qualification (document check via anabin) and an admission test.
The admission test consists of multiple-choice questions in the areas of calculus, linear algebra, probabilities and the foundations of computer science. You also have to write an essay of 200 to 300 words. We do not offer a sample test.
For admission you need English skills at level B2. By the end of your studies, you must also be able to demonstrate German language skills at level A2. You can find the exact language requirements here
There is no obligation to attend lectures in the first two semesters. However, it is up to the lecturers how they make their materials available online (live participation in the lecture, recording the lecture or uploading the teaching materials).
No. You must be on site at DIT for ALL exams.
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 | |
Foundations of Computer Science | 4 | 5 | |
Operating Systems and Networks | 4 | 5 | |
Introduction to Artificial Intelligence | 4 | 5 | |
Key Competencies 1 | 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 Competencies 2 | 4 | 5 | |
3. Semester | SWS | ECTS | |
Databases | 4 | 5 | |
Statistics | 4 | 5 | |
Project Management | 4 | 5 | |
Assistance Systems | 4 | 5 | |
AI Programming | 4 | 5 | |
Key Competencies 3 or German | 4 | 5 | |
4. Semester | SWS | ECTS | |
Natural Language Processing | 4 | 5 | |
Human Factors and Human-Machine Interaction | 4 | 5 | |
Machine Learning | 4 | 5 | |
Computer Vision | 4 | 5 | |
Software Engineering | 4 | 5 | |
Key Competencies 4 or German | 4 | 5 | |
5. Semester | SWS | ECTS | |
|
- | 30 | |
6. Semester | SWS | ECTS | |
Seminar Current Topics 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 Competencies V or German | 4 | 5 | |
7. Semester | SWS | ECTS | |
Compulsory Elective Module 2 | 4 | 5 | |
Compulsory Elective Module 3: AI Applications 1 | 4 | 5 | |
Compulsory Elective Module 4: AI Applications 2 | 4 | 5 | |
|
2 | 2 | |
|
12 | 12 |