Germany is the most popular European country for international students to study abroad. It is listed among the top three countries that are known for providing world-class opportunities in research. The country is the best center of learning for all who want to make a career in data science. There is a huge scope of master’s in data science in Germany as the top-level organizations and conglomerates hire post-graduates from there regularly.
Students interested in building a career in data science are attracted to the top universities in Germany. The country is second to the United Kingdom (UK) in terms of data science scope. Thousands of international students are placed every year at Apple, Microsoft, Deloitte, Infosys, HCL and Barclays after completing a course in data science. Since the demand for graduates and postgraduates in data science is high, therefore, the salaries paid to them are one of the best in the industry. MS in Data Science in Germany has gained popularity because data and its management are vital for every reputed organization. Germany has a dynamic education system and a competitive job market, making it an ideal place to pursue higher education from.
The post-graduate data science course in Germany is a two-year program and is spread across four semesters in total. Globally known faculty members and dynamic research infrastructure are the main pillars of German data science universities. The country has the best research-based curriculum, top universities, 100% placement records, an affordable cost of living and modern infrastructure. International students with a bachelor’s degree in a relevant field and full-time graduation from a recognized university are eligible for MS in data science courses in Germany.
There are both private and public universities and scholarships are granted to international students with excellent academic records. The semester fee in Germany is approximately 300-1000 Euros. The average pay scale for MS in data science postgraduates from German universities ranges from INR 36,00,000-60,00,000 annually.
To earn a living and manage the cost of living, international students can work up to 20 hours a week or 120 days around the year. This helps international students to not only gain work experience but also manage their cost of living in a foreign land.
Structure of MS in Data Science in Germany
|MASTER’S IN DATA SCIENCE|
|ELIGIBILITY||Graduation with 65%|
|TEST SCORE||IELTS: 6.0 and above|
|TOEFL: 95 or above|
|FEES||PUBLIC: NO FEES|
|PRIVATE: 300- 1000 Euros (Per Semester)|
|INTAKE||Summer and Winter|
Why study MS in Data Science in Germany?
1. Safe and friendly
Germany is a multi-dimensional country, and it is the third best country worldwide for international students to settle down. It is an ideal country for post-graduates in data science to meet people from various backgrounds and enjoy their stay.
2. Affordable education
With various public universities that offer free MS in Data Science courses, education in Germany is affordable. Private universities are not free, but scholarships and fee waivers do make education pocket friendly. The affordable fee structure in Germany helps in fulfilling the dreams of international aspirants to study abroad.
3. Prestigious data science universities
An MS degree in data science from a German university holds a lot of value and is recognized globally by the tech giants, banking sectors, multinationals, conglomerates, and manufacturing industries.
4. Lucrative internships
German universities are trying to work with global companies that regularly hire students for internships and industrial programs. This will offer international students the opportunity to gain industry exposure during the coursework.
5. Part-time work opportunities
Settling down in a foreign land is expensive. However, Germany offers work permits to students enrolled in educational courses. International students can work up to 20 hours a week or 120 days of part-time employment around the year.
6. Plenty of career opportunities
Germany has a dynamic and global job market. It is home to global sectors of technology, banking, manufacturing, IT, healthcare, and global multinationals. By the year 2026, it has been said that there will be more than 11.6 million job openings in the data science domain.
Read More: Why study in Germany?
Requirement for MS in data science in Germany
While the public universities offer free MS in data science in Germany, the eligibility and requirements for admission are high. An MS degree in data science from a German university holds global rank and repute. The number of applicants always exceeds the seats available, so the competition is intense. For international students, it is a cut-throat competition, and they must fulfil the given-below requirements for getting admission to MS in data science.
1. A well-drafted and formatted cover letter
2. Student visa
3. A minimum of 65% marks in graduation in the equivalent stream from a reputed and recognized university. Only recognized university undergraduate degrees will be accepted.
4. Score of GRE
5. Score of GMAT
6. The score of IELTS should be above 6.5
7. The score of TOEFL should be above 95 percentile
8. Copy of passport
9. Proof of funding or scholarship
10. Payment of academic fees
11. Financial proof
Read More: Germany study visa – all you need to know
International students from all over the world plan to study data science from one of the world’s top three research-based education imparting countries—Germany. During visa application, there are several documents that are important. Here are some of the documents required for applying for MS in data science in Germany:
1. Cover letter
2. Student visa
3. Mark sheets and degree of the last qualification
4. Proof of English proficiency exam scores
5. Letter of Recommendation (LOR)
6. Statement of Purpose (SOP)
8. Application form
Read More: Cost to study in Germany
Cost of MS in data science in Germany
The cost of MS in data science in Germany is negligible in public universities and scholarships can make private universities affordable too. As compared to other European countries, Germany is very affordable in terms of education and living costs. Here’s a rough estimate of the cost involved in studying MS from Germany:
Living costs in Germany
1. Rent and utilities: 323 Euro
2. Network: 31 Euro
3. Transport: 41 Euro
4. Food: 168 Euro
1. Visa: 75 Euro
2. English Proficiency Test: 156 Euro
3. Application form: Varies
1. Learning material: 42 Euro
2. Public universities are free.
3. Private universities’ average fee is between 300-1000 Euros (Per Semester).
Now that it has been established that Germany is the top study abroad destination for those who want to pursue postgraduation in data science, it is time to learn about the best university to pursue the course from.
Top university in Germany for MS in Data Science
University name: International University of Applied Sciences, Germany
Duration: 2 years
Students can also choose upGrad Abroad’s pathway program to pursue MS in Data Science from IU, Germany. The students will need to complete the first year online at IIIT Bangalore. For the second year, the learners will be required to travel to Germany to finish the course on-campus at IU, Germany.
Read More: Study in Germany for free
MS in Data Science in Germany: FAQs
Q1. Which are the best specializations in data science?
Data Science is a huge subject and there are various specializations available in German universities. Some of them are Advanced Machine Learning, Advanced SQL, Python, EDA, Machine Learning, Database, Advanced Visualization and Advanced Business Solving.
Q2. What are the admission intakes at German universities?
German universities conduct admissions during the winter and summer season. There are two international intakes in an annual year.
Q3. What are the main job openings in data science in Germany?
Data Science is in huge demand in Germany. The most popular job openings are Data Scientists, Business Analysts, Data Analysts, Python Developers, AI Developers, Data Engineers, Business Intelligence Analysts, Marketing Analysts, SQL Developers, Quantitative Analysts, Operation Analysts and Project Managers.