Inhalt des Dokuments
Lecture Series "Digital Future" 2019/2020
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The lecture series "Digital Future" covers different aspects of the digital transformation and aims at conveying a basic understanding of the topic. On a weekly basis, selected speakers will present subjects from their research area, covering different facets of digitalization as well as different scientific disciplines. As such, the lecture series underlines the far-reaching significance of the digital transformation. In this year's Data Science Edition, the lecture series puts an emphasis on a data-driven digital transformation. The lectures will cover two main aspects: data engineering and applied data science. The lecture series explicitly addresses all students at TUB. It thus contributes to an interdisciplinary education at TUB. Students will acquire an overview of methods and applications in the area of data-driven digital transformation. This is the first step to become "data literate."
As a lecture series, this module is organized as a sequence of weekly lectures by various lecturers, both from TU Berlin and from other institutions.
The lecture series takes place on Tuesday, at 4-6 pm in room BIB 014 (Universitätsbibliothek, Fasanenstr. 88). The first meeting is scheduled for 22 October 2019. Note that there will be no lecture on 15 October 2019.
The lecture series has a strong interdisciplinary focus and is thus open to all students at TU Berlin. It may be especially beneficial to Bachelor students. Note that, while no formal background knowledge is required for participation, technological advances in the digital world constitute the core theme of the lecture series.
You can earn credit points for your studies since this module can be included into your studies of free choice ("freier Wahlbereich"). The course is worth 3 LP. There will be an online assessment ("ePrüfung") at the end of the semester.
In order to join the lecture series, you need to enroll to the ISIS course .
to become a Data Scientist (in 3 steps)||Timm
|29.10.19||Challenges in the application
of data protection regulations in connection with the further
development of electronic commerce||Martin
|05.11.19||Data Preparation for
Data Science||Felix Naumann||HPI/UP|
|19.11.19||Data Quality in Machine
Learning Production Systems||Felix
|26.11.19||Structures, Algorithms, Data: What Do the Humanities Count
On?||Hans-Christian von Herrmann||TUB|
|03.12.19||Privacy in Database
Systems: Approaches and Their Limits||Johann-Christoph Freytag||HUB/ECDF|
Data-driven Analysis of Operational Processes||Matthias Weidlich||HUB|
|17.12.19||Paint the Black Box
White: Bias and Transparency in Machine Learning||Helena Mihaljević||HTW/ECDF|
|– lecture-free period
Data Science Is Changing Our Understanding of Perioperative
Care||Felix Balzer||Charité/HUB/ ECDF|
|21.01.20||The Promises and
Challenges of the Big Data Era in Biotechnology||Vera Meyer||TUB|
Interpretability Matters – Machine Learning In Genomics and
|04.02.20||Digital Future of
Application-Oriented Weather and Climate Research||Dieter Scherer||TUB|
Technische Universität Berlin, HUB:
Humboldt-Universität zu Berlin, ECDF:
Einstein-Center Digital Future, HPI:
Hasso-Plattner-Institut, UP: Universität Potsdam,
Beuth: Beuth Hochschule für Technik Berlin,
HTW: Hochschule für Technik und Wirtschaft Berlin,
MDC: Max-Delbrück-Centrum für Molekulare Medizin