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Digital studieren – Wir sind bereit
Präsenz- und Online-Studium, das waren bis zur Corona-Pandemie zwei getrennte Welten an der FH Kiel. Mit Start des Sommersemesters hat sich das jedoch schlagartig geändert: Die Lehre wurde innerhalb kürzester Zeit ins Internet verlagert. Mit verschiedenen Formaten kann das Studium nun auch erfolgreich von zu Hause aus absolviert werden.
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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 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.

Letzte Bewertungen

4.7
Damlare , 20.01.2023 - Data Science (M.Sc.)
4.4
Omid , 17.12.2022 - Data Science (M.Sc.)
5.0
Alex , 07.12.2022 - Data Science (M.Sc.)
4.9
G. , 21.09.2022 - Data Science (M.Sc.)
4.8
Daniel , 21.09.2022 - Data Science (M.Sc.)

Studiengangdetails

Regelstudienzeit
3 Semester tooltip
Unterrichtssprachen
Englisch
Abschluss
Master of Science
Link zur Website
Inhalte

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
Voraussetzungen
  • 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 55% in the Quantitative Reasoning part of the test.
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Studienmodelle

Bewertung
100% Weiterempfehlung
Bewertungen
Weiterempfehlung
100%
Unterrichtssprachen
Englisch
Creditpoints
90
Studienbeginn
Sommer- & Wintersemester
Standorte
Kiel
Hinweise
  • 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.
Link zur Website
Bewertung
100% Weiterempfehlung
Bewertungen
Weiterempfehlung
100%
Voraussetzungen
Contract with a cooperation partner of the Kiel University of Applied Sciences
Unterrichtssprachen
Englisch
Creditpoints
90
Studienbeginn
Sommer- & Wintersemester
Standorte
Kiel
Link zur Website

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: Fachhochschule Kiel 2022

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: Fachhochschule Kiel 2022

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: Fachhochschule Kiel 2022

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: Fachhochschule Kiel 2022

All information on application details and requirements can be found here.

For further information please contact:

Prof. Dr. Dirk Frosch-Wilke
dirk.frosch-wilke@fh-kiel.de
+49 (0)431 210 3516

Quelle: Fachhochschule Kiel 2022

Videogalerie

Studienberater
Anna-Maria Utzolino
Leitung Studienberatung
Fachhochschule Kiel
+49 (0)431 210-1761

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Allgemeines zum Studiengang

Hast du dich schon einmal gefragt, warum Streamingdienste dir immer genau die passenden Vorschläge ausspielen? Oder wie ein Algorithmus funktioniert, der frühzeitig den Verschleiß eines Bauteils erkennt? Wenn dich genau solche Fragen interessieren und du dir vorstellen kannst, diesen Themen auf den Grund zu gehen, ist ein Data Science Studium genau das Richtige für dich.

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Very practical

Data Science (M.Sc.)

4.7

I just completed my first semester. What I love most about the programme is the practical content, with sufficient theory, of course.
It is well suited for those who are most interested in learning how to use Data Science to solve real-life practical problems.

The programme is quite intense since lectures are held all day from Monday to Wednesday. The advantage of this, however, is that students have the...Erfahrungsbericht weiterlesen

What we learn is what we'll use

Data Science (M.Sc.)

4.4

I find the program very good because of the structure. Courses and their contents are designed in a way that we'll use them in work and real-life. Everything we learn, we'll learn how, when, and why it will be useful for us. In general, the program is great and I enjoy it.

Very good! Different and interesting , useful

Data Science (M.Sc.)

5.0

I'm a first semester student. it's a new and challenging program for me. but the teachers do everything to make the learning process productive and comfortable. I really like the atmosphere in the classes. The course program is intensive. We do a lot of practical exercises in the class and at home.

Kleiner neuer Studiengang

Data Science (M.Sc.)

4.9

Zum Studiengang:

Ich habe erst die ersten Vorlesungen hinter mir, bin bisher aber sehr zufrieden. Die Professoren sind alle sehr freundlich und die Semestergröße sehr klein, wodurch es sehr persönlich zugeht. Der Einstieg in die einzelnen Vorlesungen verlief langsam und Grundlagen wurden wiederholt, das finde ich besser so, damit alle auf einem Wissensstand sind. Auch ein Programmiervorkurs wurde angeboten. Zu den einzelnen Vorlesungen werden Übungsaufgaben/Übungseinheiten eingebunden, wodurch man den...Erfahrungsbericht weiterlesen

Verteilung der Bewertungen

  • 4
  • 8
  • 2
  • 2 Sterne
    0
  • 1 Stern
    0

Bewertungsdetails

  • Studieninhalte
    4.6
  • Dozenten
    4.7
  • Lehrveranstaltungen
    4.6
  • Ausstattung
    4.6
  • Organisation
    4.4
  • Bibliothek
    3.9
  • Digitales Studieren
    4.7
  • Gesamtbewertung
    4.5

Weiterempfehlungsrate

  • 100% empfehlen den Studiengang weiter
  • 0% empfehlen den Studiengang nicht weiter

Standorte

¹ Alle Preise ohne Gewähr
Quelle: Headerbilder: großes Bild Moritz Boll; kleines Bild: Matthias Pilch
Profil zuletzt aktualisiert: 07.2022