Study Type

graduate

Admission semester

Summer and Winter Semester

Target group

The offer of a consecutive Master degree program in Data Science is intentionally aimed at graduates of a broad spectrum of Bachelor programs, since Data Science competences are of great importance for very different industries. Some basic knowledge of Mathematics / Statistics and Computer Science are required.

Annotation

The students deepen their technical, methodological and social skills, especially in the areas of data storage, consolidation, processing, analysis and forecasting, with a focus on Big Data and machine learning processes. Data protection and security are also part of the training. Thus, after completing your studies, you are ideally prepared to work in the various organisational units of companies by purposefully analysing the mass of data available today and building on this, making forecasts that enable new business models and evaluate existing business models. Also possible as a degree course with practical training (PBS). For more information see https://www.fh-kiel.de/studium/studienangebot/duales-studium/praxisbegleitetes-studium/

Admission modus

Without admission restriction

Admission requirements (Link)

Admission requirements

Entrance is awarded to applicants who have completed a Bachelor's degree course with a grade of at least 2.5 and can also demonstrate 30 cumulative credit points (ECTS) in the subject areas "Mathematics/Statistics" and "Computer Science". At least 10 credit points (ECTS) must be demonstrated in the subject area "Mathematics/Statistics" and at least 10 credit points (ECTS) in the subject area "Computer Science". If the previous degree is worth fewer than 210 but at least 180 CP, the shortfall will have to be made up. A total of 300 CP should be achieved. Evidence of English language proficiency of at least level B2 of the Common European Framework of Reference for Languages (CEFR). Recognised proofs can be found in Art.7 of the Examination Regulations for the Master Program Data Science.

Fees

Fees (Link)