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Lecture Series "Digital Future" 2019/2020

[Banner] Lecture "Digital Future" 2019/2020
Lupe

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."

General Information

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.

Program Overview

Schedule
Date
Topic
Speaker
Affiliation
22.10.19
How to become a Data Scientist (in 3 steps)
Timm Teubner
TUB/ECDF
29.10.19
Challenges in the application of data protection regulations in connection with the further development of electronic commerce
Martin Haase
TUB
05.11.19
Data Preparation for Data Science
Felix Naumann
HPI/UP
12.11.19
Data Cleaning
Ziawasch Abedjan
TUB
19.11.19
Data Quality in Machine Learning Production Systems
Felix Biessmann
Beuth/ECDF
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
10.12.19
Process Mining: 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 –
07.01.20
Predictive Control
Sergio Lucia
TUB/ECDF
14.01.20
Health Data Science or How to Make Better Decisions for Critically-ill Patients
Felix Balzer
Charité/HUB/ ECDF
21.01.20
The Promises and Challenges of the Big Data Era in Biotechnology
Vera Meyer
TUB
28.01.20
Computational Genomics
Uwe Ohler
MDC
04.02.20
Digital Future of Application-Oriented Weather and Climate Research
Dieter Scherer
TUB
11.02.20
Reinforcement Learning
Klaus Obermayer
TUB

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

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Contact:

Prof. Dr. Florian Tschorsch