

MS Data Science at Kiel UAS Overview
The Kiel University of Applied Sciences MS Data Science course, recognized as a top course in the university. Students who are looking for admission, can complete their course within the duration of 18 months.
To enroll at the course, students are required to submit certain important documents which may vary on various factors including the country of origin, qualification and more. The documents required at the Kiel University of Applied Sciences for the MS Data Science include academic qualification, test scores, English language test results, interview, CV and others. The English language tests accepted at the university are IELTS, TOEFL and GRE. Students looking for admission are suggested to enroll as early as possible because the availability of the seats is limited.
However, other than tuition fee, students should also manage their budget for food, books, supplies, utilities, etc.
Duration | 18 months Get Curriculum |
Tuition & Fees | |
International Students Admission Website | Go to Website |
Official Career Service Website | Go to Website |
Course Level | PG Degree |
- Overview
- Fees
- Curriculum
- Entry Requirements
- Application Process
- Highlights
- Scholarships
MS Data Science at Kiel UAS Fees
As part of the Kiel University of Applied Sciences fee structure for the MS Data Science, students have to pay no tuition fees. However, they have to pay some one-time costs to the university at the time of admission. Other additional expenses that the students have to incur during their stay include books and supplies charges, rent, food, utilities, etc.
Find more details about Kiel University of Applied Sciences MS Data Science fee breakup, from the table mentioned below:
Fees components | Amount (for 1 year) |
---|---|
Tuition & fees | INR 0 |
Fees components | Amount (for 1 year) |
---|---|
Insurance | INR 1,15,170 |
Mandatory Fees | INR 62,820 |
MS Data Science at Kiel UAS Curriculum
Candidates interested in the Kiel University of Applied Sciences MS Data Science course can easily download the detailed curriculum by clicking the green button below. The disciplines that will be taught during the program, the different electives that students can select from, and other crucial course material are all included in one extensive PDF. It also includes a synopsis of the course structure per semester, which helps potential students see how their academic path will develop over time.
Download exam sample paper
MS Data Science at Kiel UAS Entry Requirements
- No specific cutoff mentioned
- CGPA - 2.5/5
- Read less
- Requirements
- access to the “Data Science” master’s program is granted to those who have completed a bachelor’s program with a grade of at least 2.5 and can also prove 30 cumulative credit points (ECTS) in the subject “Mathematics / Statistics” and “Computer Science” At least 10 credit points (according to ECTS) in the subject area "Mathematics/Statistics" and at least 10 credit points (according to ECTS) in the subject area "Computer Science" must be proven.
- if the previous course comprised less than 210 credit points, but at least 180 credit points, the missing skills must be made up. As a rule, a total of 300 credit points should be achieved. Applicants will be informed of the skills to be made up and the latest possible time for their proof of achievement at the beginning of the course by the examination board.
- Requirements

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Out of 10
- No specific cutoff mentioned
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Calculate your score and check your eligibility at over 2000+ universities.
Out of 10
- Marks - 5.5/9
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- No specific cutoff mentioned
- with a minimum percentile of 55% in the Quantitative Reasoning portion of the test
- Applicants with a bachelor’s degree from outside the Bologna Area (member of the European higher Education Area) also require proof of the following qualification:
- a GRE with a minimum score of 55% in the Quantitative Reasoning part of the test.
MS Data Science at Kiel UAS Application Process
MS Data Science at Kiel UAS Highlights
- The students of the interdisciplinary master’s degree in data science not only learn how to use machine learning and artificial neural networks for accurate forecasts.
- They will also develop an overall understanding of how the topics of data management, processing, analysis and visualization can be used profitably in data science projects.
- The students learn the content based on real use cases and can improve their knowledge using the relevant technologies and programming languages. They are well prepared to shape the future as data scientists in a wide variety of industries.
MS Data Science at Kiel UAS Scholarships
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