collageLudwig-Maximilian University of Munich (also referred to as LMU or the University of Munich, in German: Ludwig-Maximilians-Universität München) is a public research university located in Munich, Germany. The University of Munich is among Germany’s oldest universities. Originally established in Ingolstadt in 1472 by Duke Ludwig IX of Bavaria-Landshut, the university was moved in 1800 to Landshut by King Maximilian I of Bavaria when Ingolstadt was threatened by the French, before being relocated to its present-day location in Munich in 1826 by King Ludwig I of Bavaria. In 1802, the university was officially named Ludwig-Maximilians-Universität by King Maximilian I of Bavaria in his as well as the university’s original founder’s honour. The University of Munich has, particularly since the 19th century, been considered as one of Germany’s as well as one of Europe’s most prestigious universities; with 36 Nobel laureates associated with the university, it ranks 17th worldwide by number of Nobel laureates. Among these were Wilhelm Röntgen, Max Planck, Werner Heisenberg, Otto Hahn and Thomas Mann. Pope Benedict XVI was also a student and professor at the university. The LMU has recently been conferred the title of “elite university” under the German Universities Excellence Initiative.
Required documents
When applying for admission to Ludwig Maximilian University of Munich in Germany you should prepare all required documents. Request a list of necessary documents directly from a university, as it may vary for different countries. Using our live chat, you can also ask for sample documents.
- All Academic Documents
- Online Application form
- IELTS Certificate
- TOEFL Certificate
- Passport
- Contact No
- Email Id
- Photographs
- Proof of fee payment
- Application fee
- Local Language Certificate
- Health and Life Insurance
- Student visa
- Declaration for financial support
- Motivation Letter
- Research proposal outline (MA, PhD)
- Supervisor Agreement Form (PhD)
Data Science
Join our program MSc Data Science at Ludwig-Maximilians-Universität (LMU) Munich. LMU Munich is the first university in Germany that offers an elite graduate program in Data Science in English.
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 program is part of and is supported by the Elite Network of Bavaria.
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.
MSc Data Science – University of Munich (LMU)
The University of Munich or Ludwig-Maximilians-Universität München (LMU) is offering a 2 years Master of Science (MSc) degree in Data Science. LMU Munich is the first university in Germany that offers an elite graduate program in Data Science in English.
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 program is part of and is supported by the Elite Network of Bavaria.
The curriculum of the elite master’s program Data Science is a modularised study program. Students learn statistical and computational methods for collecting, managing, and analyzing 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, 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.
Admission Requirements
- 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.
- Proficiency in English: at least B2 CEFR (or equivalent); or English university entrance qualification; or first degree in English.
Candidates need to fulfill all the requirements if they want to apply.
Course Structure
The curriculum of the elite master’s program Data Science is a modularised study program. Students learn statistical and computational methods for collecting, managing, and analyzing 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.
Curriculum Overview
Statistics: Inference and Sampling (12 ECTS) – First and Second Semester
The core module Statistics covers fundamental statistical concepts and methods and consists of two courses.
Informatics: Knowledge Discovery and Big Data Management (12 ECTS) – First and Second Semester
The core module Informatics gives an overview of the steps of the knowledge discovery process and consists of two courses.
Fundamentals of Data Science (12 ECTS) – First Semester
Each student will be assigned to two courses from a variety of courses in advanced methods of statistics and informatics. These comprise lectures on statistical modeling, multivariate data analysis, advanced programming, and database systems, in regression modeling and multivariate data analysis, among others. At the end of the module, students will be on a homogeneous level of expertise in both statistics and informatics.
Human Computation and Analytics (9 ECTS) – First and Second Semester
The module Human Computation and Analytics covers those aspects of Data Science, in which humans either produce data, and process and analyze it with the help of algorithms, or in which data are presented to humans by a computer system.
Predictive Modelling (6 ECTS) – Second Semester
Predictive Modelling, in particular by means of non-linear, non-parametric methods, has become a central part of modern data analysis both in computer science and statistics in order to uncover complex patterns and relationships in data.
The module covers models such as decision trees, neural networks, support vector machines, and ensembles (random forest, bagging, boosting) and concludes with advanced techniques regarding model selection, feature selection, and hyperparameter optimization.
Data Ethics and Data Security (6 ECTS) – Second and Third Semester
The Data Ethics and Data Security module covers basic legal and ethical questions and challenges of data security.
Elective Modules (12 ECTS) – Second and Third Semester
In the elective modules, students may choose courses in specialized fields from the regularly offered master courses in statistics, informatics, and computer linguistics. In addition, students may also attend master-level courses at the partner universities. These include courses on image processing at TUM, computational finance at Augsburg University, and mathematical statistics at TUM.
Current Research in Data Science (9 ECTS) – Second and Third Semester
In this module, publications of current research in Data Science will be discussed. Students will learn to work independently with scientific publications and to present newly acquired scientific knowledge. This module also comprises the summer schools, the focused tutorials, and the DataFest.
Data Science Practical (12 ECTS) – Third Semester
The module Data Science Practical plays a central role in the curriculum of the master program. Practical experience with data-analytic methods that are taught in the core and elective modules is essential in order to generate knowledge from data.
Students will work on practical problems in the field of data science. The problems are typically concrete projects provided by non-university partners. The focus of the course is therefore not only on tackling methodological challenges in the analysis of massive data (Big Data) but on communicating the results and findings to the client.
Master thesis and disputation (30 ECTS) – Fourth Semester
The master thesis concludes the study program. The thesis may be either research-orientated or stimulated through a practical problem, e.g. as an extension of a data science practice.
Tuition Fees
There is no tuition fee for this program, but a fee for student services and the basic semester ticket.
In Germany, students don’t have to pay tuition fees for most degree programs. However, you might want to look for a student job (of which there are plenty) or apply for a scholarship to finance your studies in Munich.
Scholarships
As an international student, you are eligible for several scholarships and funding opportunities throughout Germany and the State of Bavaria. You can also count on the support of institutions like the Munich Student Union.
“Assistance in Case of Financial Difficulty” Scholarship
Eligibility:
International students and doctoral candidates at the LMU, who find themselves in short-term and unexpected financial need, can apply for one-time financial assistance ($731), funded by the State of Bavaria, at the International Office at LMU.
For the application you need the following documents:
Scholarship Application Deadline: 30 November
Requirements
Qualification Requirements
Previous Degree
Bachelor’s degree (or equivalent) in statistics or informatics or related disciplines. Excellent knowledge of computer science and statistics. Applicants need to provide evidence of knowledge in the following fields:
- Statistical science and data-based modeling: this includes, in particular, statistics and topics such as data mining, probability theory, and machine learning (at least 30 ECTS or equivalent). (Average grade n° 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 n° 3).
Required ECTS credits: 180.GPA Rate 1.50GPA Comment
The overall average grade must be better than 1.5. The overall average grade is composed of:
- Average grade 1: the average grade from the best performance (equivalent to 150 ECTS).
- Average grade 2, and
- Average grade 3.
Additional information: English language proficiency can also be proven by an English university entrance qualification or a first degree in English.
Application & Admission
Application Deadlines
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For Candidates with previous degree fromWinter Semester
(starting in October)Summer Semester
Applications are open from:April 16 (German)April 16 (EU)April 16 (Non EU)
Application Procedure & Selection
Mode of admission:local admission restriction Admission test/interview:interviewApplication:directly at University Application Fee:none
Application Documents
The following documents must be submitted by all applicants via the portal:
- Transcript of records.
- Bachelor certificate (if not yet available, it needs to be provided no later than September 30th).
- Essay “Data science” (in which you look at the developments and perspectives of data science as well as your planned area of specialization, and your previous experience; max. 1,000 words).
- Proof of proficiency in English (see language requirements).
When you start your online application you will see the details on the information and the type of documents required.
You may also submit other documents that may be relevant for the application (e.g. certificate of enrolment or course certificates/credits from earlier study programs, vocational certificates from the IT sector).
Documents which are not in German or English must be provided as a certified translation.
Please note: the university only accepts online applications. Please do not send any documents by email.
International applicants
Applicants who do not hold German citizenship and have obtained their certificates and degrees from non-German institutions have to apply simultaneously to the LMU International Office.
Online Application for the MSc Data Science
The deadline for the online application for the winter semester 2022/2023 was 1 June 2022.
Please read the information on our website carefully.
Before you start your application: Please read the requirements on our website carefully. Your application will only be considered if you meet all requirements. Also read the FAQ on our website carefully before you start your application.
The following documents must be submitted by all applicants via the portal:
- Transcript of records
- Bachelor certificate (if not yet available, it needs to be provided no later than 30 September 2022)
- Essay “Data Science” (in which you look at the developments and perspectives of Data Science as well as your planned area of specialisation, and your previous experience; max. 1,000 words)
- Proof of proficiency in English (see requirements)
When you start your online application you will see the details on the information and the type of documents required.
You may also submit other documents that may be relevant for the application (e.g. certificate of enrolment or course certificates / credits from earlier study programmes; vocational certificates from the IT sector).
Documents which are not in German or English must be provided as a certified translation.
Please note: We only accept online applications. Please do not send any documents by email.
Information for applicants: If you have submitted your application online (first step in the application process), you will be informed by email before the end of June whether your online application was successful.
If your online application is successful we will invite you for an interview (second step in the application process). Interviews (personal or via videoconference) will take place at the end of June/beginning of July. Invitations to the interviews (with date and time) will be sent out by email at least one week before the scheduled interview date. Information on whether your interview was successful will be sent out in mid-July.
International applicants
Applicants who do not hold German citizenship and have obtained their certificates and degrees from non-German institutions have to apply simultaneously to the LMU International Office.
(International Office, Ludwigstraße 27, 80539 München). For further information, click here: German, English
The aptitude assessment and the application to the International Office are two independent processes. The International Office reviews the qualifications obtained abroad in order to certify whether the applicant is eligible to study at LMU Munich. However, the International Office will not make a decision regarding the aptitude of the student and subsequent admission to the specific study courses.
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