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Data Science (M.Sc.)

Taught in German

Overview

Data Science
Data Science

Foto: ismagilov/123rf.com
Overview

Overview

Data science, the analysis of large amounts of data, e.g. using artificial intelligence and machine learning methods to extract usable information, has become an integral part of today's society. This also requires constant further development of existing methods and research into new concepts in order to meet the constantly growing demand and increasing complexity of the areas of application. This is where the Master's degree programme in Data Science at JLU comes in.

Bachelor's graduates from the Data Science degree programme, as well as related degree programmes such as Applied Computer Science or from computer science degree programmes at other universities, are taught in-depth knowledge of mathematics and programming as well as advanced methods of data analysis in the first year of studies in order to prepare them for the requirements of the more research- and project-oriented second year. The focus here is on project work on the topics of data science and artificial intelligence, as well as a specialisation module, which can also be completed as part of a professional internship. The final module is the Master's thesis, which may build on the previously completed professional internship or specialisation module in terms of topic and content.

The exact module composition and course of study is individually developed with the respective applicants, taking into account the qualifications already acquired in the Bachelor's degree programme, whereby a comprehensive catalogue of compulsory electives offers extensive opportunities for individual profile development. This ensures that all graduates of the Master's degree programme in Data Science are equally qualified for future scientific research activities and relevant management positions in industry and business.

 

Composition

Composition

Duration of Studies

4 Semesters - 120 Credits Points

Composition of Studies

Composition of Studies

The Master's degree programme in Data Science is open to different Bachelor's degrees such as Data Science, Applied Computer Science and Computer Science. In order to take this diversity into account, an individual study plan is drawn up for the respective applicants, taking into account the qualifications already acquired in the Bachelor's degree programme.

Generally, the core of the programme consists of:

  • three blocks, from each of which a minimum number of CP must be taken (see below)
  • an area of specialisation
  • the professional internship/specialisation module
  • the Master Thesis

The three blocks of the programme's core, in which a total of at least 48 CP must be acquired, are:


Block A: Methods of Data Analysis (min. 24 CP):

  • Artificial Intelligence I (9 CP)
  • Artificial Intelligence II (9 CP)
  • Project – Artificial Intelligence (9 CP)
  • Visualisation of Information (9 CP)
  • Advanced Data Analytics (9 CP)
  • Project – Data Science (9 CP)
  • Basics of Data Analysis in R (6 CP)
  • Statistics and Simulation in R (6 CP)
  • Linear Models in R: Regression and Variance Analysis (6 CP)

Block B: Programming (mind. 9 CP):

  • Object-oriented Programming for Data Science (9 CP)
  • High Performance Computing (9 CP)

Block C: Mathematik (mind. 6 CP):

  • Quantitative Foundations of Artificial Intelligence (6 CP)
  • Topological Data Analysis (9 CP)
  • Numerics (9 CP)

In the area of specialisation (12 - 30 CP depending on the study plan) you have a wide choice of courses from different subject areas (e.g. law, economics, archaeology, mathematics, physics, psychology, geography, medicine, chemistry).

You can find sample study plans here.

Application

Application: Entrance Requirements

Commencement of Studies

Possible during the Winter and Summer Semester.

 

Admission Requirements

The following Bachelor's degrees are accepted for the enrollment of this course of study:

  • Data Science
  • Applied Computer Science
  • Computer Science

The board of examination may also recognise other degrees upon a case-by-case inspection.

Enrollment

Application/Enrollment

No NC (GPA) requirements apply to this course of study.

Start of Enrollment Period for the Summer Semester
  • 05.12.2023
End of Enrollment Period for the Summer Semester
  • 20.03.2024 for persons with a german university entrance qualification
  • 29.02.2024 for persons with a foreign university entrance qualification

Start of Enrollment Period for the Summer Semester 2024/25
  • 01.06.2024
End of Enrollment Period for the Summer Semester 2024/25
  • 01.09.2024 for persons with a german university entrance qualification
  • 15.08.2024 for persons with a foreign university entrance qualification

Different rules may apply to international applicants. Mehr

Career Options

Perspectives

Doctoral Studies

  • Doctorate possible after the successful completion of the Master's degree.

Career Fields

The collection, analysis and evaluation of data is becoming increasingly important and has become an integral part of many scientific and application areas. The latter include, for example, market analyses and risk assessments, as used by banks and insurance companies, but also analyses of internet users and customers in order to carry out targeted advertising.

Rapid developments in the field of data science are taking place in medicine, transport and manufacturing. More and more large companies are turning to data-driven analyses in order to optimise processes, improve products or develop new products. The latter includes the production of new materials. In science, large amounts of data (for example in particle physics) are traditionally processed and analysed in experiments at large accelerator facilities. This is also the case in astronomy and climate research.

In recent years and decades, more and more scientific disciplines have recognised that data-driven research not only represents a pure increase in efficiency, but can also bring new insights to light. For this reason, there are now many activities in the field of data science - across disciplines from the natural sciences and life sciences to the humanities and cultural sciences.

Modern research and development teams are interdisciplinary and bring together different areas of expertise. Data-driven research and development requires data scientists in such a team, although there are currently only a few graduates from universities.

Exciting applications, in addition to the further development of existing methods and research into new concepts in the university environment or at research institutes, can be found in areas such as:

  • Medicine: gene data analysis, tumour detection, pandemic simulation, ...
  • Natural science: particle physics, climate modelling, new materials, ...
  • Sociology: Social Media, Social Dynamics & Processes, ...
  • Financial sector: algorithmic stock exchange trading, credit analysis, fraud detection, ...
  • Linguistics: speech recognition, text generation, sentiment analysis, ...
  • Online trade: buyer profiles, customised product suggestions, market analysis, ...
  • Industry: Process optimisation, product development, ...
  • Logistics: goods cycles, transport planning, ...

Further Information

Further Information: Documents

Links

Master's Degree Programmes of Faculty 07

International

Information for outgoing students

Information and consultation

 

Information for incoming students

Information and consultation

 

Contact

Student Counselling
Subject Advisors

Prof. Dr. Christian Heiliger

Institute for Theoretical Physics
Heinrich-Buff-Ring 16, room 441
35392 Gießen
Phone: 0641 - 99 33360
E-mail: Christian Heiliger

Links

Contact

Beate Pitzler
(Student counselling)

Student Hotline "CallJustus"
(Initial information on all questions relating to the degree programme, Phone: 0641-9916400)

International Office - Contact Persons and Office Hours
(Counselling and support for international students and applicants)

 

 
Keywords
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