Founded on the idea of empowering people to succeed in a digital world, the International University of Applied Sciences first came into existence in 1998. And since receiving accreditation from the German Council of Science and Humanities, IU’s grown into Germany’s biggest university. The university's mission is to create inclusive, global and wholly accessible education.

IUAS is one of Germany's leading private Universities of Applied Sciences. IU International University of Applied Sciences place a strong emphasis on quality. That is why all of the institution's study programs are state-approved, bears the seal of German Accreditation Council and are globally recognised.

Applied Artificial Intelligence tools are becoming a larger presence in our everyday lives, and will continue to do so for years to come. Many people use them without even realizing it, when talking to chatbots, and for many, the interactions with personal digital assistants such as Alexa or Siri have become second nature. But Applied AI offers so much more; it’s the key to groundbreaking technologies that are expected to completely change our lives, like self-driving cars.

Companies who will act fast and incorporate this technology in their business strategy, have a real chance of taking over entire market shares. That’s where students, as future Applied AI specialist, come into the picture.

Accreditation: 
IU is accredited and certified with a seal of approval from the German Accreditation Council. All IU study programmes, materials, and services meet high internal and external quality standards, which are regularly reviewed and updated.

Scholarship:
• Scholarship Programme 
• Deutschlandstipendium (German scholarship)

First Semester:
Artificial Intelligence
Introduction to Academic Work
Introduction to Programming with Python
Mathematics: Analysis
Collaborative Work
Statistics: Probability and Descriptive Statistics

Second Semester:
Object oriented and functional programming in Python
Mathematics: Linear Algebra
Intercultural and Ethical Decision-Making
Statistics - Inferential Statistics
Cloud Computing
Cloud Programming

Third Semester:
Machine Learning - Supervised Learning
Machine Learning - Unsupervised Learning and Feature Engineering
Neural Nets and Deep Learning
Introduction to Computer Vision
Project: Computer Vision
Introduction to Reinforcement Learning

Fourth Semester:
Introduction to NLP
Project: NLP
Introduction to Data Protection and Cyber Security
Data Science Software Engineering
Project: From Model to Production
Seminar: Ethical Considerations in Data Science

Fifth Semester:
User Experience
UX-Project
Project: Edge AI
Introduction to Robotics
Agile Project Management
Electives A

Sixth Semester:
Electives B
Electives C
Bachelor Thesis