Teaching

Due to advances in data availability and computing power, machine learning (ML) applications are becoming increasingly important for both industry and public institutions. Examples include HR managers using ML predictions to assess the future job performance of applicants during the hiring process, insurance agents using ML to calculate risk premiums of potential customers, banks using ML to assess the default risk of borrowers, and judges relying on algorithmically generated risk assessments to make bail decisions. Against this backdrop, it is increasingly important to understand how modern ML methods work and how they can support decisions.
This course provides an introduction to the workings, opportunities, and risks of using ML applications to support management decisions. Topics covered include data preparation, integration, analysis, Supervised ML, and the importance of ML applications in decision making processes. Students will implement and apply the methods using the Python programming language and associated libraries.

This seminar focuses on exploring state-of-the-art research topics in the domain of human interactions with Artificial Intelligence and eXplainable Artificial Intelligence systems. Students have to write a seminar paper about a specifically assigned research topic and present their work in class for discussion. 

Application via email (Brief motivation letter, Transcript of Records and CV) to kevin.bauer@uni-mannheim.de;

Application deadline: until 12.02.2024 – 23:59.

Notification of acceptance: until 14.02.2024 – 11:59.

Eligible withdrawal: until 15.02.2024 – 11:59.

Topic assignment: 19.02.2024

Submission of seminar thesis: until 15.04.2024 – 23:59.

Presentation of seminar thesis: TBD (Remote via Zoom).

This seminar focuses on exploring the latest issues related to generative artificial intelligence (e.g., large language models such as ChatGPT). In the seminar paper, students will explore the economic, psychological, and sociological consequences of using this new technology.

Students have to write a seminar paper about a specifically assigned research topic and present their work in class for discussion. 

Application via email (Brief motivation letter, Transcript of Records and CV) to kevin.bauer@uni-mannheim.de;

Application deadline: until 12.02.2024 – 23:59.

Notification of acceptance: until 14.02.2024 – 11:59.

Eligible withdrawal: until 15.02.2024 – 11:59.

Topic assignment: 19.02.2024

Submission of seminar thesis: until 15.04.2024 – 23:59.

Presentation of seminar thesis: TBD (Remote via Zoom).

The seminar in Applied Data Science is a unique, project-based course designed for Masters students who are looking forward to immersing themselves in the world of real-world data analysis and solution development. This seminar is characterized by an exciting collaboration with Coface, a leading global credit insurance group (www.coface.com). In addition to the credit insurance business, Coface operates factoring with Coface Finanz GmbH and is also a leader in this field in Germany. Factoring is a financial transaction in which a company sells its trade receivables (i.e. invoices) to a third party, the so-called factor. This process provides the company with immediate cash flow, which is crucial for maintaining liquidity and financing day-to-day operations. Coface will provide students with access to current, industry-relevant factoring datasets and offer an unprecedented opportunity to apply data science techniques in a practical context.

Application via email (Transcript of Records and CV) to kevin.bauer@uni-mannheim.de;

Application deadline: until 12.02.2024 – 23:59.

Notification of acceptance: until 14.02.2024 – 11:59.

Eligible withdrawal: until 15.02.2024 – 11:59.

Topic assignment: 19.02.2024

Submission of seminar thesis: until 15.04.2024 – 23:59.

Presentation of seminar thesis at Coface in front of the company board: TBD .