Kurzbeschreibung
The interdisciplinary Master's Program Data Science at FH Kiel teaches a comprehensive and versatile hands-on approach to Data Science. Students develop and apply a broad understanding of machine learning (incl. artificial neural network...
The interdisciplinary Master's Program Data Science at FH Kiel teaches a comprehensive and versatile hands-on approach to Data Science. Students develop and apply a broad understanding of machine learning (incl. artificial neural networks), data management, protection, and security, stream processing, data analysis, visualization, and ethics. Module content is taught using real-world use cases and state-of-the-art technology. Courses teach necessary theoretical foundations but the main focus is on hands-on experience: All exams are practical tasks and projects. Next to various lecture modules, an application project is organized in cooperation with industry partners.
The program explicitly invites practitioners and students from various fields of study (extensive previous knowledge on programming or computer science is not required). Through interactive courses, we bring their different perspectives together and engage students in discussion and exchange of experiences and knowledge.
Studiengangdetails
Semester 1
- Cloud Computing
- Data Management
- Data Visualization and Visual Analytics
- Machine Learning
- Mathematics and Multivariate Statistics
- Tools and Programming Languages for Data Science
Semester 2
- Application Project
- Big Data Technologies
- Deep Learning
- Elective Module
- Social Media Analytics
Semester 3
- Colloquium
- Thesis
- access to the “Data Science” master’s program is granted to those who have completed a bachelor’s program with a grade of at least 2.5 and can also prove 30 cumulative credit points (ECTS) in the subject “Mathematics / Statistics” and “Computer Science” At least 10 credit points (according to ECTS) in the subject area "Mathematics/Statistics" and at least 10 credit points (according to ECTS) in the subject area "Computer Science" must be proven.
- if the previous course comprised less than 210 credit points, but at least 180 credit points, the missing skills must be made up. As a rule, a total of 300 credit points should be achieved. Applicants will be informed of the skills to be made up and the latest possible time for their proof of achievement at the beginning of the course by the examination board.
- evidence of English language skills that correspond to at least level B 2 of the Common European Framework of Reference for Languages. Example of accepted evidence can be found in Section 7 of the Examination Regulations for the master’s degree in Data Science.
Applicants with a bachelor’s degree from outside the Bologna Area (member of the European higher Education Area) also require proof of the following qualification:
- a GRE with a minimum score of 65% in all parts of the test (Verbal Reasoning, Quantitative Reasoning und Analytical Writing)
Studienmodelle
- Studies & Job: The program’s schedule is designed to allow flexible coordination and combination of studies and job (see below: Studies & Job).
- Students with only 180 ECTS from their previous studies need to collect 30 ECTS from courses of their choice (e.g. language courses, courses from application domains, etc.). in addition to the 90 ECTS of the regular course program.
Studienberatung kontaktieren
Du hast Fragen zum Studiengang? Deine Nachricht wird direkt an die Studienberatung weitergeleitet.
The program is ideally suited for students with jobs. More than 70% of our students work part-time.
- Lectures take place on only three days a week, leaving two days possible office attendance.
- Lectures are distributed over twelve weeks per semester.
- Exams take place mostly during the lecture period.
- All compulsory lectures start every term, allowing for a flexible arrangement beyond the minimum three semesters.
- The master thesis can be written in cooperation with industry partners, e.g. one’s employer.
Quelle: HAW Kiel - Hochschule für Angewandte Wissenschaften
The program explicitly welcomes students from all over the world! The courses are held in English and all material is available in English. Exams and thesis can written in English (or optionally in German). Applicants will provide evidence of their command of English, e.g. through school certificates, TOEFL, Cambridge- ESOL, or other.
Quelle: HAW Kiel - Hochschule für Angewandte Wissenschaften
Courses focus on relevant theoretical and methodical aspects as well as on their practical implementation. Starting in the first lessons, students will create various types of data science applications using their own notebooks. Thus graduates will have practical experience and the ability to implement data science solutions on their own.
A dedicated application project is part or the second term’s curriculum. Here students work in teams on actual real-world data science projects from our partners in industry. Industries include banking, energy, health, logistics, media, telecommunications, and more. The teams are supervised both by members of the respective companies as well as by their professors.
An overview of past application projects can be found here.
Quelle: HAW Kiel - Hochschule für Angewandte Wissenschaften
The program explicitly invites students from all kinds of disciplines. Neither a comprehensive IT background nor knowledge about programming are required. Instead, applicants must have earned 30 ECTS in the fields of math/statistics and computer science (with at least 10 ECTS from each field). Relevant basics like math, programming, or databases are taught in the first semester of the curriculum as well as in a dedicated (non-mandatory) warm-up course.
Quelle: HAW Kiel - Hochschule für Angewandte Wissenschaften
All information on application details and requirements can be found here.
For further information please contact:
Prof. Dr. Tillmann Schwörer
tillmann.schwoerer@fh-kiel.de
+49 (0)431 210-4541
Quelle: HAW Kiel - Hochschule für Angewandte Wissenschaften
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Social Media
Gut gerüstet für den Berufseinstieg
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Praxisnahes Studium mit top Zukunftsperspektiven
Das Studium im Bereich Data Science bietet eine hervorragende Mischung aus theoretischen Grundlagen in Mathematik und Statistik sowie praktischer Anwendung in der Programmierung mit Python und R. Die Dozenten sind meist sehr engagiert und bringen viel Praxiserfahrung aus der Industrie mit, was die Vorlesungen sehr anschaulich macht.
Super organisiert bisher
Erstes Semester im Master. Alle vorgesehenen Pflichtvorlesungen wurden auf Montag bis Mittwoch gelegt, sodass man nebenher noch arbeiten kann. Alle Vorlesungen finden in den selben 2 Räumen statt. Profs sind nett und Motiviert zu Lehren. Sehr viele Kommilitonen die aus nicht Informatik/Statistik nahen Studienrichtungen kommen (Psychologie, Maschinenbau, ...). Dementsprechend können einige Inhalte im ersten Semester repetitiv sein.
Ansonsten scheint mir der Studienverlauf sehr durchdacht mit vielen Inhalten, die aufeinander aufbauen.
Excellent and well-rounded Data Science Program
The Data Science degree program has been an exceptionally rewarding experience. The study content is very thorough, covering essential areas such as Mathematics for Machine Learning, Machine Learning, Deep Learning, Programming Tools, Data Visualization, Data Engineering, and more, while also including practical, hands-on projects and research opportunities through the thesis that prepare students for real-world challenges. During the application projects and thesis work, students have the opportunity to collaborate with...Erfahrungsbericht weiterlesen
Weiterempfehlungsrate
- 93% empfehlen den Studiengang weiter
- 7% empfehlen den Studiengang nicht weiter
Standorte
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Standort Kiel
HAW Kiel - Hochschule für Angewandte Wissenschaften
Sokratesplatz 1
24149 Kiel
VollzeitstudiumData Science - industriebegleitet / dual studies