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Overview

Overview

Data Science is the science of extracting knowledge and information from data and requires competencies in both statistical and computer-based data analysis. The elite program Data Science is an interdisciplinary program and is carried out jointly by the Department of Statistics and the Institute for Informatics at LMU Munich. 

The curriculum of the elite master program Data Science is a modularised study program. Students learn statistical and computational methods for collecting, managing, and analysing large and complex data sets and how to extract knowledge and information from these data sets. The program also comprises courses on data security, data confidentiality, and data ethics. In the practical modules students will tackle real-world problems in cooperation with industrial partners. Other highlights of the program are the summer schools and the focused tutorials.

Upon graduation our students are well prepared for a career as a data scientist in the private or public sector in fields such as applied economics, political science, sociology, education, medicine, public policy, and media research. Students may also pursue a doctoral study in a variety of academic disciplines that require quantitative analysis.

Program Structure

The curriculum of the elite master program Data Science is a modularised study program. Students learn statistical and computational methods for collecting, managing, and analysing large and complex data sets and how to extract knowledge and information from these data sets. The program also comprises courses on data security, data confidentiality, and data ethics. Other highlights are the practical modules in which students will tackle real-world problems in cooperation with industrial partners, as well as summer schools and tutorials, and the DataFest. With this training graduates of the master program will be innovative and responsible academics with excellent career opportunities both in industry and economy as well as in science and research.

Highlights of the Curriculum

  • Methodological as well as practical modules,
  • Courses on data security, data confidentiality, and data ethics,
  • Training of transferable skills,
  • Close cooperation with industrial partners.

Entry Requirement

  • Bachelor of Science (or equivalent) in Statistics or Informatics or related disciplines (at least 180 ECTS or equivalent).
  • Excellent knowledge in Informatics and Statistics. Applicants need to provide evidence of knowledge in the following fields:
    • Statistical Science and Data-Based Modelling: This includes, in particular, statistics and topics such as data mining, probability theory, and machine learning (at least 30 ECTS or equivalent). (Average Grade 2)
    • Computer Science and Computational Methods: This includes, in particular, data structures and algorithms, database systems, programming principles and practice, software engineering (at least 30 ECTS or equivalent). (Average Grade 3)
  • Overall Average Grade must be better than 1.5. The overall average grade is composed of (1) Average Grade 1: the average grade from the best performance (equivalent to 150 ECTS), (2) Average Grade 2, and (3) Average Grade 3.
  • Proficiency in English: at least B2 CEFR (or equivalent); or English university entrance qualification; or first degree in English.

 


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