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AI & Data Science

2. Juni 2023
AI als Stütze für die operative Compliance: Erwartung vs. Realität

Rachid Tahrioui

Artificial Intelligence (AI), Machine Learning (ML) und Robotic Process Automation (RPA) sind Begriffe, die im Finanzsektor verwendet werden, wenn es um Maßnahmen zur Prozessoptimierung, Kosten- und Zeitersparnis geht. Die Forderung nach den neuesten technologischen Entwicklungen bestimmt seit geraumer Zeit den Markt. Insbesondere bei der Bekämpfung von Finanzkriminalität plädieren Fachexperten für den Einsatz dieser Technologien. Welche Herausforderungen bringt der Einsatz von künstlicher Intelligenz mit sich? Wie steht die BaFin zu diesem Thema und welche Auswirkungen könnte dies auf die operative Compliance zur Folge haben? Mit diesen Fragen gilt es, sich kritisch auseinanderzusetzen.
19. Januar 2022
AI Pontryagin or how neural networks learn to control complex systems
Lucas Böttcher
Optimal control of complex dynamical systems can be challenging due to cost constraints and analytical intractability. In our work, we propose a machine-learning-based control framework able to learn quasi-optimal control signals and steer complex high-dimensional dynamical systems towards a desired target state.
Many democratic societies have become more politically polarized, with the U.S. being the main example. The origins of this phenomenon are still not well-understood and subject to debate. In a recent study, we analysed the mechanisms underlying political polarization using survey data that has been collected by the Pew Research Center from 1994 to 2017.
20. Mai 2021
Drivers of political polarization in the USA from 1994 to 2017
Lucas Böttcher
6. April 2020
AI for Business: In guten wie in schlechten Zeiten
Michelle Neumann
Unternehmen weltweit haben es gerade sehr schwer. Durch die Ausbreitung des Coronavirus und den damit verbundenen Auflagen sehen sie sich vor eine große, existenzielle Herausforderung gestellt. Es gibt während dieser globalen Krise auch Bereiche, die die Ereignisse als Chance nutzen können, vorallem im Bereich der Digitalisierung.
Bei Datenanalysen in den Bereichen Ökonomie und Business spielt das Verständnis, die Selektion und die Aufbereitung der Daten eine entscheidende Rolle, um gute und valide Ergebnisse zu erzielen.
7. Februar 2020
Zur Notwendigkeit von Domänenwissen in Data Science Studiengängen
Peter Roßbach
18. Dezember 2020
Responsible AI?

Prof. Dr. Sebastian Köhler

In the near future, we can expect such systems to be able to carry out more and more tasks all by themselves. Apart from self-driving cars, it is likely that we will encounter autonomous machines in many places: in warehouses, hospitals, banks, and on the battlefield.
16. März 2020
Technik, die Leben rettet? AI im Kampf gegen das Coronavirus

Michelle Neumann

Frühzeitige Erkennung der Anzeichen könnte die Wendung bringen: Der chinesische Konzern Alibaba entwickelt AI-Innovation für den schnellen und effizienten Nachweis des Coronavirus.
16. August 2019
Why I chose the Master in Applied Data Science
Zakariya Abu-Grin
I have always been interested in computers, but I ended up studying petroleum engineering. A main reason for this is that the oil industry was one of few options in my country Libya with international exposure. My dream has always been to have a fast-growing career, work with different people and travel to different countries.
This year I got the chance to participate in the conference for the “Gesamtbanksteuerung 2019”, with the central topics regulation, digitalization, and Artificial Intelligence (AI).
15. Juli 2019
Is Artificial Intelligence a game-changer for banks?
Matthias Ilg
27. Juni 2019
Deep Learning: becoming a data scientist and fulfilling your creative potential
Prof. Dr. Florian Ellsäßer
The improvement of deep learning is even more surprising, as previous algorithms had only made gradual progress for many tasks where it had excelled.
The analytical thought process and decision making, cultivated in me over 3 years of professional experience in analytics has been instrumental in my success. However, to upgrade and explore in the multi-disciplinary sphere of data, pursuing a master in data science was my obvious choice.
29. März 2019
Gamification in the Master in Applied Data Science
Nupur Kulkarni
19. September 2019
Nowcasting Inflation: Machine Learning to resolve the classification challenge?

Lukas Henkel

Understanding inflation dynamics is crucial for the conduct of monetary policy. However, official inflation statistics are published only with a time lag. Hence, central bankers are interested in “nowcasting” inflation, among other variables. Nowadays we have data on prices of individual products posted every day on the internet.
10. Juli 2019
The most sought after profession: Data Scientist

Prof. Dr. Florian Ellsäßer

It is important to update knowledge of the existing workforce as a data scientist in companies. Regardless of this lack of “human-like” cognitive intelligence, there are a great number of potential applications. Find out about educational programmes.
29. Januar 2019
From Biology to Applied Data Science
Theresa Pareno
The rapid development of technology has impacted almost every industry and almost all scientific fields. It is one of the catalysts in the biggest innovation from science to business. From editing a human embryo and growing an organ from a stem cell for donations to making medical robots that are 1000 times smaller than a human hair to suffocate tumors and potentially storing the data in our DNA. All of these are just examples of how far one field can go through the aid of technology.
Machine Learning has a very simple definition but its application can literally be a game-changer for many companies. With the advent of the blockchain, artificial intelligence and data analytics technologies
9. April 2018
When Machines Talk: Machine Learning and Analytics permeate into the finance market
Prateek Shukla
AI als Stütze für die operative Compliance: Erwartung vs. Realität
2. Juni 2023
Rachid Tahrioui
AI Pontryagin or how neural networks learn to control complex systems
19. Januar 2022
Lucas Böttcher
Drivers of political polarization in the USA from 1994 to 2017
20. Mai 2021
Lucas Böttcher
Responsible AI?
18. Dezember 2020
Prof. Dr. Sebastian Köhler
AI for Business: In guten wie in schlechten Zeiten
6. April 2020
Michelle Neumann
Zur Notwendigkeit von Domänenwissen in Data Science Studiengängen
7. Februar 2020
Peter Roßbach
Technik, die Leben rettet? AI im Kampf gegen das Coronavirus
16. März 2020
Michelle Neumann
Why I chose the Master in Applied Data Science
16. August 2019
Zakariya Abu-Grin
Is Artificial Intelligence a game-changer for banks?
15. Juli 2019
Matthias Ilg
Nowcasting Inflation: Machine Learning to resolve the classification challenge?
19. September 2019
Lukas Henkel
Deep Learning: becoming a data scientist and fulfilling your creative potential
27. Juni 2019
Prof. Dr. Florian Ellsäßer
Gamification in the Master in Applied Data Science
29. März 2019
Nupur Kulkarni
The most sought after profession: Data Scientist
10. Juli 2019
Prof. Dr. Florian Ellsäßer
From Biology to Applied Data Science
29. Januar 2019
Theresa Pareno
When Machines Talk: Machine Learning and Analytics permeate into the finance market
9. April 2018
Prateek Shukla