Praktikum Big Data Science

Aktuelles
  • Due to the circumstances we will conduct this practical course using Zoom instead of personal meetings until further notice.
    Additional details are given in the kickoff meeting.

    Zuletzt verändert: Di 07 Apr 2020 00:00

Beschreibung

Big Data and Data Science gain increasing attention and significance, as they are discovered by scientific and economic domains. Today Data Science and Big Data advance into various facets of our daily life. The purpose of this practical course is to make the students familiar with the practical approach of Big Data applications and Data Science. By learning the handling with state-of-the-art Big Data tools the core concepts of the Big Data process are conveyed.

In particular, the students will work on Deep Learning approaches in various different data domains, including image, text, point clouds and graphs. Besides the aspects of data-driven analysis, this course aims to foster the practice of agile project management methods and the application of software engineering techniques. Furthermore, this course targets the responsible and efficient handling of limited resources.

Eligibility Requirements

As the lab course will cover several advanced topics in data science and big data analytics, successful participation in at least two of the following lectures or similar prior experience is recommended:

  • Knowledge Discovery in Databases I
  • Knowledge Discovery in Databases II
  • Machine Learning
  • Deep Learning

The lab course requires skills and experience in programming and software engineering. It is beneficial to be experienced with

  • git (also GitLab)
  • Linux Server (using a shell, ssh)
  • Python (in particular numpy, pandas, sklearn, pytorch)

Please explain in the form how you meet the requirements and describe relevant practical experience.

Institut
Institut für Informatik
Dozent:in
Assistent:innen
Kursteilnehmer:innen
28 von 30
Zentralanmeldung
Masterpraktika
Anweisungen zur Bewerbung

Please explain how you meet the requirements and describe relevant practical experiences in the following

form

Material

Das Kursmaterial ist nur für Mitglieder des Kurses einsehbar, also z.B. für Teilnehmer:innen, Tutor:innen, Korrektor:innen und Verwalter:innen.

Prüfungen
NameNameAnmeldung abAnmeldung abAnmeldung bisAnmeldung bisTerminTerminPrüfungsanmeldungPrüfungsanmeldung
Nicht zur Prüfung angemeldet
Termine
ArtArtZeitZeitRegulärer RaumRegulärer RaumNotizNotiz
Kick-Off Meeting
  • Mi 22 Apr 2020 14:15–17:45
Remote
Global Session
  • Mi 06 Mai 2020 16:00–18:00
  • Mi 20 Mai 2020 16:00–18:00
  • Mi 03 Jun 2020 16:00–18:00
  • Mi 17 Jun 2020 16:00–18:00
  • Mi 01 Jul 2020 16:00–18:00
  • Mi 15 Jul 2020 16:00–18:00
Remote
Final Presentation
  • Mi 22 Jul 2020 14:00–18:00
Remote