Master in Applied Data Science

We encourage you to submit your application as soon as possible to benefit from our Earlybird discounts. Just keep in mind that the application must be complete to be eligible. 

*In order to secure the Early Bird 1 discount you must have received an admission letter by the 31 March

**In order to secure the Early Bird 2 discount you must have received an admission letter by 30 June

Knowledge and understanding (broadening, deepening and understanding of knowledge)

Graduates will have in-depth knowledge and a critical understanding of the key theories, principles and methods in Data Science. They will be able to identify, analyse and evaluate complex data problems.

This competency is particularly relevant to and developed in the core modules, such as Algorithms and Data Structures, Introduction to Data Analytics in Business or Computational Statistics and Probability and via various means of teaching, learning and assessment (e.g. projects, programming assignments or exam).

Usage and development of knowledge

Graduates will have the ability to construct and critically assess computational, data-driven models to solve complex data problems in Business.

The application of analytical techniques is at the core of almost all modules in the programme. The Master in Applied Data Science encourages not only to learn, but rather to apply models to the classroom (e.g. Machine Learning I and II or Deep Learning).

Communication and cooperation

Graduates will be able to communicate effectively in academic and/or private business contexts. They will formulate technical problem solutions and represent them in discourse. They are responsible team members who address and reflect different perspectives.

These competencies are practiced in many modules such as Introduction to Data Analytics in Business or Guided Studies in Financial Management in which students have to do several week-long projects in order to understand and apply the knowledge and skills they have gained in the module. This competency is furthermore at the core of the Cooperation Company Project. Our students are able to test the knowledge they have learned in previous semesters by working on real business use cases together with leading companies in the Cooperation Company Project. Over a period of approx. two months, students will work closely and cooperatively with the company from the start to finish of the project, thus gaining end-to-end, hands-on professional and personal experience. 

Scientific self-image and professionalism

Graduates are practiced collaborators in business environments. They have a thorough understanding of their ethical and legal responsibilities as applied data scientists. They will base their professional activities on theoretical and methodological knowledge.

The development of these competencies is distributed throughout the curriculum and in consequence, follows the natural student journey as they grow academically and professionally. The culmination of students’ individual awareness of their role in Business and Society can be found in their final project, the thesis, and in the core module AI & Humanity – The Ethics of Data Science. On successful completion of this module, students will have a thorough comprehension of central legal and ethical issues surrounding information technologies, as well as the crucial legal and ethical questions we must ask about such technologies. Students will furthermore be able to identify and evaluate legal and ethical problems related to information technologies, develop and critically assess appropriate responses to such problems, and assess their own evaluative outlook critically. Finally, students will have developed and strengthened their analytic and critical skills, as well as their ability to apply those skills to solve ethical and legal problems.

Inspired by data analyses in motorsports, a team of PwC data scientists and data engineers came up with the idea to build a slot car racing track equipped with several sensors to show data analytics possibilities at exhibitions.

The key aspects of their project were:

• Creating an image recognition that is able to identify the two race cars in a video stream captured by a camera placed next to the track.
• Developing new ways of controlling and monitoring the cars.
• Splitting the existing project backend into modular domain specific backends.
• Creating a central communication service that is responsible for information exchange between the frontend, the backends and the cloud.

You can follow their project blog including video updates from start to finish here.

Students worked on a market trends project to understand market sentiment and investor activity across Xetra and Eurex. Project topics included; clustering data, predictive power and analysing relationships between datasets. They used data science and machine learning to assess predictability and ultimately visualise the data with which a report was produced. You can read the Market Trend Insights report here for further information.

Accenture

Carl Zeiss AG

Clearstream - Deutsche Börse Group

Deloitte

Deutsche Bank AG

Deutsche Börse

EY

Finbourne

Formlabs GmbH

GIZ

KMPG

McKinsey & Company

Merck KGaA

proresult Unternehmensberatung AG

• Certified copy of your undergraduate transcript of records and degree award certificate
• Certified copy of your TOEFL / IELTS results or equivalent (TOEFL - 90 iBT, IELTS 7.0 or equivalent)
• Official GMAT score report, GRE score report or FS Admissions Test
• CV or resume (must be in English)
• Other documentation supporting professional experience or other extracurricular activities, if applicable

Each of the documents listed above are required for completing your application. However, you do not need to upload them all at once.

Applications are considered on a rolling basis, therefore we encourage you to apply as early as possible. Applications received before the end of November and March will benefit from our early bird discounts of EUR 4,000 and EUR 2,000 respectively. Applicants interested in a scholarship must complete the relevant section within their online application.

*You must have received an admission letter by 31 March and 30 June respectively

Total fees: EUR 35,750 (including enrolment fees)

Deposit: EUR 3,000 (deducted from the total tuition fees)

The remaining fees will need to be paid in regular instalments at the beginning of each semester. Should you decide to opt for a full upfront payment, you will receive a 5% reduction on tuition fees (excluding discounts).

Please note that the tuition fee's exclude any additional costs i.e. travel expenses, hotel costs for modules abroad.

You can contact Proresult directly if you would like to know more about the position.

Contact:

Andreas Peters

andreas.peters@proresult.de