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Data Engineering and Analytics

Technical University of Munich

M.Sc.
24 months
Duration
Free
Free
Unknown
Tuition fee
Unknown
Apply date
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Start date

About

The master's degree program in Data Engineering and Analytics at Technical University of Munich deals with innovative solutions for handling and analyzing very large amounts of data.

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Overview

Handling and analyzing very large amounts of data is an urgent problem in many areas of science and industry and requires novel approaches and techniques. The trend towards "Big Data" is caused by a host of developments: Firstly, the creation and storage of large data sets becomes feasible and economically viable, for example due to price decreases in storage space, sensors, smart devices, social networks and many more. 

Secondly, technical advances for example in multi-core systems and cloud computing make it possible to examine data sets at large scale. And thirdly, such amounts of data do not only origin in the "classical" domains like business data, but now are created in many areas of life. Consider vehicles, that create sensor data and share information via intelligent networking, or consider data that is created by intelligent energy grids.

Which professional opportunities can I take up with this qualification?

  • The master’s programs “Mathematics in Data Science” and “Data Engineering and Analytics” offer access to many career opportunities including: research, consulting, IT security, systems design, and data science in industry. 
  • The respective departments offer Ph.D. positions that are the pathway to a career in research. Typical job profiles in industry include data analysts and data engineers. Data engineers master very large databases and distributed information systems and are responsible for IT security and applied data analytics for structuring data. 
  • Data analysts filter and extract information from large data sets based on statistical and mathematical methods and tailor them towards informed strategic decisions

Programme Structure

  • The curriculum comprises mandatory courses on Data Analysis and Data Engineering. Advanced lectures are offered in these area of studies: Data Engineering contains lectures about distributes systems, distributed databases, query optimization, database systems on modern CPU architectures and high performance computing.  
  • Data Engineering and Analytics offers lectures about machine learning, business analytics, computer vision and scientific visualization. Data Analysis is concerned with topics that require solid mathematical foundations: Fundamentals of Convex Optimization, Computational Statistics and more.

Key information

Duration

  • Full-time
    • 24 months

Start dates & application deadlines

Language

English, Partially taught in German
IELTS or TOEFL needed

Credits

120 ECTS

Delivered

On Campus

Academic requirements

GPA admission requirements GPA Your GPA, or Grade Point Average, is a number that indicates how well or how high you scored in your courses on average. Usually a GPA scales between 1.0 and 4.0, however different countries and universities can have different grading systems.
GRE admission requirements GRE® The GRE® General Test is a widely administered admissions test that measures the skills needed in today's graduate and business school programs worldwide. It contains three sections - Verbal Reasoning, Quantitative Reasoning, and Analytical Writing. Three scores are reported: a Verbal Reasoning score on a 130 - 170 score scale in one-point increments, a Quantitative Reasoning score on a 130 - 170 score scale in one-point increments, and an Analytical Writing score on a 0 - 6 score scale in half-point increments.
GMAT admission requirements GMAT The Graduate Management Admission Test (GMAT) is a test intended to assess certain analytical, writing, quantitative, verbal, and reading skills in written English for use in admission to a graduate management program, such as an MBA. GMAT contains 4 sections - Analytical Writing Assessment, Integrated Reasoning, Quantitative and Verbal. The score has a range from 200 - 800.

English requirements

IELTS admission requirements IELTS The International English Language Test System (IELTS) tests your English-language proficiency on a scale of 1 – 9. The score refers to the combined average score of 4 subjects (writing, listening, speaking, and reading).
6.5 (required)
TOEFL admission requirements TOEFL® IBT The TOEFL iBT® is given online through the internet at desiganated testing site. The test measures your English-language abilities in an academic setting. The score refers to the total score of 4 subjects (writing, listening, speaking, and reading), each subject has a range of 0 - 30.
88 (required)
PTE Academic admission requirements PTE Academic PTE Academic (Pearson Test of English Academic) is a language test that enables students to demonstrate their writing, listening, speaking, and reading skills when applying to study in English. The score refers to a total score which ranges between 10 and 90.

Other requirements

General requirements

  • Online Application Print-out (signed)
  • Transcript of Records (certified copy)
  • Proof of English Language Proficiency (certified copy)
  • Complete and Current Résumé (CV)
  • Letter of Motivation
  • Essay
  • Analysis of Curricula
  • Module Catalog
  • Most Current Photo (as for ID)
  • Passport (copy)
  • Student Health Insurance Certificate
  • Preliminary evaluation by uni-assist for graduate certificates (i.e. a bachelor's degree) obtained in a country outside of the EU/EEA

Tuition Fee

  • International

    Free
    Tuition Fee
    Based on the original amount of 0 EUR per semester and a duration of 24 months.
  • EU/EEA

    Free
    Tuition Fee
    Based on the original amount of 0 EUR per semester and a duration of 24 months.

Funding

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

Our partners

Data Engineering and Analytics M.Sc.
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Technical University of Munich

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