About Data and AI: Lecture Series Data Literacy

  • type: Lecture (V)
  • chair: General Studies. Forum Science and Society (FORUM)
  • semester: WS 26/27
  • time: Wed 2026-11-11
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)


    Wed 2026-11-18
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2026-11-25
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2026-12-02
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2026-12-09
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2026-12-16
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2027-01-13
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2027-01-20
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2027-01-27
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2027-02-03
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2027-02-10
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)

    Wed 2027-02-17
    15:45 - 17:15, weekly
    50.28 Seminarraum 2
    50.28 InformatiKOM 2 (EG)


  • lecturer: Prof. Dr. Senja Post
    KIT-interne und externe Dozent*innen
  • sws: 2
  • lv-no.: 11300340
  • information: On-Site
Content

The lecture series helps students from all disciplines expand their data literacy. Through interdisciplinary lectures and discussions, participants develop a basic understanding of how data is collected, processed, managed, analyzed, and applied.

In a series of rotating lectures, experts from within and outside KIT address the most important aspects of data analysis and use, providing insights into research and science while always considering the risks and societal implications.

Following each presentation, there will be time for discussion, and attendees will have the opportunity to engage in conversation with the experts.

No prior knowledge of the subject matter is required to participate. Students and doctoral candidates from all disciplines are invited, as are interested individuals who have registered for specific sessions (dataliteracy@forum.kit.edu ).

The detailed program can be found here: www.forum.kit.edu/dali.

2 – 3 CP

Language of instructionGerman/English
Organisational issues

Anmeldung erforderlich über: https://plus.campus.kit.edu/signmeup/procedures/6994