Requirements and target group for the Master's distance learning programme in Data Science (M.Sc.)

With your M.Sc. in Data Science, you could work, for example, as a Data Scientist, a Data Science Consultant, or a Data Science Developer

The Master's distance learning programme in Data Science at IU International University of Applied Sciences is aimed at individuals who have already completed a basic degree in Data Science, Computer Science, Mathematics, Statistics, or a closely related field and want to expand their knowledge to an advanced level. This programme is particularly suitable for you if you are pursuing a career in data-based analysis, machine learning, or big data, such as working as a Data Scientist, Data Engineer, or in analytical specialist and leadership positions. The study is entirely flexible and therefore ideal if you want to pursue further education alongside work, during a break, or from any location worldwide.

Admission requirements

Degree and grade:

• You need a completed Bachelor's, Diplom, or equivalent basic degree from a state or state-recognized university, comprising a minimum of 180 ECTS or 240 ECTS.
• Your primary degree should have a clear focus on Data Science, Computer Science, Mathematics, or Statistics.
• The minimum grade for admission is "Satisfactory" (according to the German grading system, grade 3.0 or better).
• For the 60-ECTS variant, one year of relevant work experience after the primary degree is also required.

Alternatives to the minimum grade: Admission is possible with a Bachelor's degree with the grade "Sufficient" (up to 4.0) if you can provide evidence of relevant Master's modules (at least 40 ECTS or 20 ECTS) or already hold a relevant Master's degree or an equivalent non-university qualification recognized at DQR7 level.

Non-related primary degree: If your primary degree does not focus on any of the areas mentioned above, you can meet the entry requirements through a Master's entry examination. You must successfully complete two defined modules within 12 months.

Language skills:

• For the English-language programme: Proof of English proficiency (e.g., TOEFL from 80 points, IELTS from Level 6 or equivalent certifications). Alternatively, a completed English-language primary degree or English mother tongue is also acceptable.
• For international applicants to the German study programme: Proof of German language skills at least at B2 level (e.g., TestDaF, Telc B2, or equivalent certificates).

In addition to the formal requirements, IU International University recommends the following personal requirements for a successful Master's study in Data Science:

• Solid mathematical basic knowledge and an interest in statistics, algorithms, and data analysis.
• Solid understanding of basic programming techniques, ideally with some experience in Python.
• Independent and structured work approach, as distance learning requires a high level of self-organization.
• Affinity to digital tools and learning platforms to make optimal use of multimedia offers and AI-supported learning environments.
• Motivation to analyze complex issues from science and business in a data-based manner and develop innovative solutions.
• Curiosity about new technologies and willingness to continuously educate yourself on current developments in Data Science and Artificial Intelligence.

Master Data Science at IU: Content, Skills, and Specializations Overview

In the Master's programme Data Science at IU International University, you will deepen your knowledge of data analysis, programming, and Artificial Intelligence. The programme combines conceptual foundations with practical applications. You will deal with innovative technologies and learn to analytically solve complex data-driven challenges in business, research, or technology.

Subject Areas:

• Statistics and advanced mathematics for Data Science
• Programming, especially with Python
• Machine Learning and Deep Learning
• Big Data technologies and data infrastructure
• IT security and data protection
• Software engineering for data-intensive applications
• Data Science Use Cases, practical projects, and case studies

Elective Areas:

• Specializations such as Data Engineering, IT project management, or Industrial Automation
• Thematic specializations, e.g. NLP and Computer Vision, Reinforcement Learning, or IoT
• Business-oriented modules like Change Management, Global Branding, Sales, and Strategic Finance

Thesis: In the Master's thesis, you will work on an independent scientific project in the field of Data Science.

During the course of your studies, you will develop the following skills, among others:

• Critical analysis and evaluation of complex data sets
• Independent implementation of data-driven projects – from data acquisition to modeling and interpretation
• Application of software development methods to data science problems
• Shaping new technologies in areas such as AI, Big Data, or digitization of business processes

Organizational Structure and Study Model – How the Data Science Distance Learning Works

The Master's programme is entirely online and follows the IU's distance learning concept:

• You can choose between different time models: Full-time (24 months), Part-time I (36 months), or Part-time II (48 months). Switching between them is flexible during the study programme.
• The programme consists of modules, each of which is worked on and completed separately. Exams can be taken as online assessments 24/7 – completely independent of location.
• You determine the start of your studies: Enrollment is possible at any time, there are no fixed semester times.
• All teaching materials (scripts, interactive books, videos) are available digitally on the online campus and in the IU Learn App. You can also use printed materials.
• In interactive online lectures and virtual tutorials, you will exchange ideas with lecturers and fellow students.
• Examination forms range from traditional exams to projects, assignments, and presentations. Open-book formats are also possible.
• Optionally, you can shorten the duration of your studies or save on tuition fees through the recognition of previous achievements.
• The learning platform provides access to an extensive online library, AI-supported learning assistants, and numerous additional offerings such as LinkedIn Learning or office tools.
• An obligatory internship is not provided for, but elective modules from the "Internship: Master AI, Machine Learning and Data Science" area can be taken.

Career Perspectives: These Career Options are Available to You

With a Master's degree in Data Science, you enter a broad and dynamic field of work. The demand for data experts is growing across industries – especially in the technology sector, finance, industry, the health sector, and research. Typical job profiles include:

• Senior Data Scientist: Analyzing complex data, developing algorithms, leading Data Science teams
• Data Science Developer: Developing data analysis tools and AI applications, implementing machine learning projects
• Data Engineer: Building and expanding data pipelines, data management infrastructure, connecting large data sets
• Data Architect: Designing and optimizing company-wide data architectures
• Other roles: Technical Project Lead, Business Analyst, AI Consultant, or Data Consultant

After graduation, you are capable of working both in a scientific-research and practical-applied manner in companies, start-ups, or public institutions. The Master's degree is internationally recognized and qualifies you for leadership positions or further academic careers (e.g., promotion).

Costs, fees and financing options

The costs for the Data Science distance learning programme (60 ECTS) vary depending on the chosen time model:

• Full-time (12 months): 775 € per month – total costs approx. 10.099 €
• Part-time I (18 months): 575 € per month – total costs approx. 11.149 €
• Part-time II (24 months): 475 € per month – total costs approx. 12.199 €

Regular discount promotions offer savings on tuition fees. The tuition includes all services such as digital learning materials, access to the online library, personal career coaching and optional live lectures. A non-binding trial month allows you to test the programme for free at the start.

• Financing options: Education funds, private student loans, tax deduction as income-related expenses and various regional funding programmes. IU also accepts individual recognition of prior learning (e.g. from previous studies or further training), which can further reduce costs.

Thanks to the digital learning concept, there are no expenses for textbooks or on-site travel. Semester breaks and extensions (up to 12 months) are available free of charge if you need more time.