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The Central State Office for Distance Learning (ZFU) has approved the course Artificial Intelligence under the number 1110220. - Standard period of study for this Master's degree is only 12 or 24 months, part-time study possible
- Interesting specializations, such as AI Specialist or UI/UX Expert
- Innovative learning concept with IU Learn App and digital teaching events
- Completely English-language distance learning programme
These are the admission requirements for the Master's programme Artificial Intelligence
We offer the Master's programme in Artificial Intelligence in 2 variants: the shortened 60-ECTS variant takes 2 semesters in full-time study. The 120 ECTS variant takes 4 semesters in full-time study.
For the 120 ECTS variant in 4 semesters, the following requirements apply:
- You have a first academic degree with a final grade of at least "satisfactory" in Mathematics, Computer Science, Natural Sciences, or Technology.
In addition, you can also enter the Master's programme without a Bachelor's degree. Details on the Master without Bachelor's at IU can be found here: Master without Bachelor's at IU: How admission to the Distance Learning Master for Professionals works.
For the shortened 60-ECTS variant, the following requirements apply:
- If your first academic degree is 180 ECTS, you take courses worth 30 ECTS afterwards and have at least 1 year of relevant work experience. Alternatively, you show at least 2 years of relevant work experience.
- If your degree is 210 ECTS, you have at least 1 year of qualified work experience. You gained this work experience after completing your studies.
- If your degree is 240 ECTS, which is the case for many diploma degrees, you also need to show 1 year of qualified work experience in addition to the degree.
- In addition, you need prior knowledge in "Advanced Mathematics," "Advanced Statistics," and "Programming with Python." You can take these courses at IU free of charge before starting your studies. Alternatively, you demonstrate equivalent prior knowledge.
You also need to demonstrate your English language skills. You can do this, for example, through a TOEFL test (at least 80 points), IELTS (at least Level 6), a passed Duolingo English test (at least 105 points), a Cambridge certificate (at least Grade B overall), or an equivalent qualification. Alternatively, you can take a free English course directly at IU International University.
All information on the requirements, content, specialization options, and costs can also be found in your personal information package for the part-time online studies in Artificial Intelligence. With the brochure, you will also receive access data for a demo account of myCampus, the online campus of IU. Request brochure now... Study Contents & Modules: This is the Study Schedule in the Master of Artificial Intelligence
The master's program at IU International University is modular. A module usually consists of 5 credits (ECTS) and concludes with an examination, such as a written assignment or an exam. You will complete your master's degree step by step - and even have the freedom to choose when to complete each module.
In the 60-ECTS version, you can structure your study plan in full-time as follows:
- 1st Semester: Machine Learning, Deep Learning, Reinforcement Learning, Inference and Causality, Elective A
- 2nd Semester: Elective B (Computer Vision and NLP, Advanced Robotics 4.0, Applied Autonomous Driving), Seminar: Current Topics in AI, Master Thesis
You can choose your first specialization module from the following topics: Applied Autonomous Driving, Foundational Computer Vision, Artificial Intelligence in FinTech, AI in Healthcare and Medical Imaging, Natural Language Processing and Voice Assistants, Industrial AI, Artificial Intelligence in Supply Chain Management, AI in E-Commerce, Marketing and Demand Forecast, AI in Healthcare and Medical NLP, AI in Healthcare and Medical Robotics, AI in E-Commerce, Marketing and Analytics, AI in E-Commerce and Customer-centric Marketing, Industrial Production Systems, Computer Vision for Production Systems, NLP and its Application in Education, NLP and its Application for Accessibility.
You can choose your second specialization module from the following topics: Functional Security and Computer Vision for Autonomous Systems, Cognitive Computer Vision, Robo Advisory and AI in FinTech, Medical NLP and Medical Robotics, NLP and Innovative Technologies in Education, Industrial Automation and Computer Vision for Autonomous Systems, AI and its Application in Demand Forecast and Procurement, AI for Analytics, Personalization and Recommender Systems, Computer Vision and NLP, Advanced Robotics, Computer Vision Essentials.
In the 120-ECTS version, you could structure your curriculum in full-time as follows:
- 1st Semester: Artificial Intelligence, Programming with Python, Advanced Mathematics, Advanced Statistics, Machine Learning, Project: AI Use Case
- 2nd Semester: Advanced Research Methods, Deep Learning, Continual Learning with Neural Networks, Seminar: AI and Society, Electives A
- 3rd Semester: Electives B, Electives C (Internship or modules to choose)
- 4th Semester: Master Thesis
In the 120-ECTS version, you choose a total of 2 specialization subjects based on your interests.
You can choose your first specialization module from the following topics: Software Engineering for Data Intensive Sciences, NLP and Computer Vision, Reinforcement Learning, Inference and Causality, Explainable and Interpretable Machine Learning Models, Seminar: Current Topics in AI, Natural Language Processing, Project: Prompt Engineering, Voice Assistants, Image Processing and Low Level Vision, Mid-Level Vision and Video, Project: Generative Deep Learning, Concepts of FinTechs and Artificial Intelligence, Corporate Governance of IT, Compliance, and Law.
You can choose your second specialization module from the following topics: Fraud Detection FinTechs, AI in Production, Project: Industrial Internet of Things, Introduction to AI in E-Commerce and Marketing, Corporate Governance of IT, Compliance, and Law, AI in Marketing and Analytics, Personalization and Recommender Systems, Demand Forecast and Inventory Control, Artificial Intelligence in Procurement, Concepts of Artificial Intelligence in Supply Chain Management, Multi-Agent Systems, Robo Advisory, NLP in Education, NLP for Accessibility, AI in Healthcare, AI in Medical Imaging and Diagnostics, Medical NLP, Medical Robotics and Devices, High-Level Vision, Project: Computer Vision, Industrial and Mobile Robots, Project: Collaborative Robotics, Architectures of Self-Driving Vehicles, Case Study: Localization, Motion Planning and Sensor Fusion, Functional Security, Computer Vision for Autonomous Systems, Modeling in Automation Engineering, Advanced NLP and Computer Vision, Project: NLP and Computer Vision, Data Engineering, Project: Data Engineering, IT Project Management, Project: Technical Project Planning, User Interface and Experience, Project: Human Computer Interaction, International IT Law, Seminar: Legal Framework for IT-Security.
For Elective C, you can choose between Internship: Master AI, Machine Learning and Data Science, or Project: Start Up Lab, Case Study: Model Engineering, Use Case and Evaluation.
Study Concept: How the Part-Time Study of Artificial Intelligence works at IU
You can adjust the online study program in Artificial Intelligence at IU International University to fit your life and daily routine as it best suits you. For example, you can choose from 3 study models: In the full-time program, it takes a total of 2 semesters or 4 semesters to complete the master's degree, depending on the study option. In part-time study I, you will complete your degree in 3 or 6 semesters. Alternatively, you can opt for part-time study II and take your time with 4 or 8 semesters to complete the master's.
With each module at IU, you receive study materials in the form of printed study booklets. All materials are also available digitally. The IU Interactive Books are innovative learning scripts enriched with video clips and quiz questions at the end of each lesson. Depending on the module, study materials are complemented by podcasts, live tutorials, and video content in the form of shortcasts. You can access the IU Interactive Books through the convenient IU Learn app.
In many modules, virtual classes are offered, enabling you to interact interactively with your peers and instructors.
A particularly practical and flexible feature is the option to take module exams in the form of online exams. You can take an online exam 24/7, 7 days a week - whenever you feel best prepared for the exam, for example, in Construction. Moreover, we operate about 40 exam centers in Germany, Austria, and Switzerland where you can also take your exams in a traditional on-site manner.
Experiences & Reviews
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The Master's programme in Artificial Intelligence (M.Sc.) at IU International University is generally well-regarded by most students, although currently only a few reviews of the programme can be found online. Students particularly praise the high flexibility of the distance learning programme and the current, practical study contents. At the same time, some criticisms are also evident: Technical issues with the online campus and inadequate support or organizational shortcomings are mentioned. Overall, the experience reports paint a mixed picture with numerous strengths, but also areas where there is room for improvement.
Study Contents: The academic quality of the master's programme is mostly highly rated. Many describe the modules as challenging and well-prepared. The topics are considered highly relevant in the field of AI and the study is strongly practice-oriented. The provided study materials - especially scripts - enable a quick overview and are praised as extensive and helpful. A large online library is available for further in-depth study. Some graduates report that for full learning success, their own research and reading are necessary. Overall, the academic quality is said to be comparable to university teaching. There is some criticism suggesting that more depth would be desirable - for example, more practical work with common AI programming libraries. These comments indicate that the programme offers a broad introduction, but specialists may seek additional depth.
Support from Lecturers: The academic support and contact with lecturers are experienced differently. Many students report competent, helpful professors and tutors. The lecturers are described as qualified and provide well-founded answers to questions. Mentoring by the university also receives praise. However, there are also negative experiences: In particular, the interaction with lecturers is sometimes considered too short. Some distance learners feel left to their own devices as feedback from support services can sometimes take a long time. Also, the exchange among fellow students is relatively limited, which restricts the sense of community. While groups exist, many find little activity or support from lecturers there.
Online Campus & Technology: The digital learning platform and various online tools are a central element of the IU distance learning programme. Reviews on this are mixed. It is noted positively that the platform overall provides a good overview of study progress and organization. Some report that the online campus runs smoothly. However, technical weaknesses are also evident: The interface is described partially as inconsistent and confusing . Some integrated tools are considered complicated and poorly thought out. Bugs and interface problems sometimes lead to delays in grading or blockages in course registration. Such problems require time-consuming contact with support. While the digital infrastructure offers many features, it is in practice partially in need of improvement.
Seminars and Online Tutorials: The live online seminars are seen as very helpful by many. Students praise them for being of high quality in terms of content and for providing the opportunity to clarify questions directly with lecturers. Interaction with fellow students is also partly achieved. However, communication outside these sessions remains limited. Some wish for more frequent tutorials or workshops. Without their own initiative, communication among students remains rather sporadic. Overall, the seminars are appreciated for their quality, but their scope and reach could be expanded.
Flexibility: The outstanding flexibility of the IU distance learning programme is almost universally emphasized. This is considered the biggest advantage of the programme. Students stress that they can optimally balance their studies, work, and personal life through the flexible schedule. There are no rigid semester times, and the learning pace can be individually adjusted. This flexibility is particularly valued by employed or family-committed students as an unbeatable advantage. The downside is that self-discipline is required. For well-motivated individuals, however, the IU model provides a highly satisfying study experience.
Value for Money: There are mixed opinions on the tuition fees and the perceived value for money. Some consider the costs to be relatively high. It is critically noted that much must be worked out independently and the personal effort of the university is comparatively low. On the other hand, many view the programme as worth its price: The quality offered and career advantages justify the costs. Particularly satisfied graduates clearly see the personal benefit as the main focus. Overall, the assessment depends heavily on expectations and financial situation - while some criticize the programme as costly, others perceive what is offered as cost-effective.
Disclaimer: This editorial review is based on an analysis of publicly available reviews, testimonials, and opinions from various sources. The summary provides an objective and factual representation of the most common positive and negative aspects as reported by current and former students. It does not claim to be complete or absolutely correct. Individual experiences may vary, and it is recommended to conduct additional research independently before making a study decision.
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