Welcome to the area of teaching and studies

We enable our students to study in a way that is both methodologically sound and very practical.

You have to bring something to the party: We expect from our students an intense, committed interest, genuine curiosity and the motivation to want to make a difference!

Our teaching concept is based on a combination of innovative teaching methods and the involvement of representatives from the business world in lectures and exercises.

Thus, we have been working very well and in partnership with companies such as Accenture, Allianz, Atvisio, Campana & Schott, Commerzbank, Deloitte, Eintracht Frankfurt, Frankfurter Allgemeine Zeitung, Fujitsu, Heraeus, Hessian Ministry for Digitalization, Invensity, Kaufland, KPMG, McKinsey, Porsche, P&G, SAP, Serviceware and many more in our teaching for many years.

In addition, we use innovative teaching methods such as case studies, agile software projects (SCRUM) and the joint development of business models.

This lecture deals with the digital transformation in different industries, for example, finance, mobility, medicine and sports.

The focus is on developing new digital business models and answering the question of how companies can make better decisions based on data.

A central theme in this lecture is the use of artificial intelligence (AI) and machine learning. Examples of AI applications will be discussed, as well as the associated challenges and ethical issues.

Several guest talks by our cooperation partners like Commerzbank, Heraeus, Eintracht Frankfurt, Heidelberger Druckmaschinen AG, Samson and Campana & Schott are integrated into the lecture in order to intensify further the practical relevance of the topics covered.

In the exercise, the contents of the lecture are deepened through case studies based on current practical examples.

This lecture (held in German) deals with the functionalities and the economic principles of the Internet and Software Industry. Strategies and business models for the internet, as well as software and cloud providers, are derived. This includes pricing, distribution, cooperation, and acquisition strategies.

The lecture opens with the specifics of the digital network economy, focusing on the characteristics of digital goods and the resulting network effects. The emerging platform economy will be illustrated with real-world examples, and current political issues will be discussed in addition. The first part of the lectures concludes with the effects of digitalization on the value chain.

Building on this, the second part deals with the essential economic principles of the software industry. One focus here is on the parameters of software pricing as well as cooperation and acquisition strategies. The unique features of the strategies of cloud and AI providers are also examined in more detail.

The last part of the lecture addresses data as the basis of business models. Here, on the one hand, privacy models from research that deal with the disclosure of data; on the other hand, the value of data for novel business models are emphasized.

To further intensify the practical relevance, the event includes guest lectures from Serviceware SE, Deutsche Bahn AG, SAP SE, Frankfurter Allgemeine Zeitung and SNP SE.

In the parallel exercise, the contents will be deepened in the context of case studies.

The goal of this lecture is to teach our students the start-up and innovation process for creating digital products and services. For more than ten years, we have been collaborating with the Israeli Reichman University (opens in new tab) (formerly IDC Herzliya) as part of this course.

The course lasts five full days and participants independently develop new business ideas and learn to evaluate and present them. Involved are also many industry partners and venture capital organizations to whom the students can present their business ideas.

The goal of the event is not only to develop new business models for digital products and services; rather, students should learn to think entrepreneurially.

The event is being held in cooperation with HIGHEST.

Project management is one of the most common tasks of our graduates in practice. Particularly in the context of digital transformation – for example in IT implementation projects – good and practice-oriented knowledge from the field of project management is a key success factor.

In this course we teach management- and technology-oriented basics of project management. One focus is on the application of agile methods. In addition, the knowledge is deepened through case studies.

In the following semester, students learn to apply their acquired knowledge in an internship. This means that they work in teams of about six to eight participants on problems from operational practice.

The following figure shows the practice partners of the IT internship from WS 21/22.

Most of the projects are specifically about developing software solutions in teams based on an adapted SCRUM framework. The chair's Jira Web Platform – a software for process and project tracking – supports the students in planning, tracking and managing their IT projects. The effort for each student is about 270 hours.

And it's worth it: the solutions developed are often successfully used by the practice partners.

This two-semester course centers around the topic of artificial intelligence and machine learning.

For many years, we have been working with our cooperation partner Porsche to realize the course. We train students in the basic knowledge required for machine learning and in the use of libraries and tools that significantly simplify the development of machine learning applications. The application area of the involved project is the topic of “After Sales”. In small hackathons, so-called “Capstone Projects”, the students develop innovative solutions for real-world problems at Porsche SE.

In the first half of the module – Artificial Intelligence I - students first gain insight into the theoretical and historical foundations of Artificial Intelligence and key machine learning algorithms.

To do so, we deal with the emergence of the AI research field, agents and search methods, modeling and solving problems with agents, knowledge processing and representation, data and knowledge modeling, expert systems and inference, as well as with the central algorithms and problems of machine learning.

Moreover, students are introduced to the Python programming language in order to implement and discuss various concepts from the lecture.

In the second half of the module – Artificial Intelligence II - the basic knowledge is further deepened.

To achieve this, we address current and practical challenges of AI use (Big Data, parallelization, transparent and fair AI, etc.) as well as functionalities of advanced algorithms and methods, such as Deep Neural Networks or generative methods.

In addition, we deeply engage with the development process of AI solutions in order to enable students to exploit potentials and to overcome possible hurdles and challenges in the realization of AI in productive scenarios.

As in the first part of the module, the implementation of the theoretical concepts in Python are discussed and exemplified along real-world applications of AI.

In this course, we give students of Business Administration/Industrial Engineering an introduction to the economical rules of the software industry and a fundamental overview of software development management and implementation. Students then learn fundamental concepts of information processing as well as the visualization of software algorithms.

Building on this, our students acquire fundamental knowledge in programming with object-oriented programming languages and become familiar with how to implement solutions in software. Finally, we deal with the differences between traditional software development and software development using machine learning. In this context, we discuss the opportunities that machine learning can bring to software development and the challenges that need to be taken into account.

We offer hands-on exercises to complement the lecture, in which students can write their own programs using the Eclipse programming environment and the Java programming language, and test their own programs in a safe way.

This lecture is about the economics of digital transformation. One focus is the platform economy – one of the most significant business models in the age of digitalization. In addition, different waves of digitalization up to the use of artificial intelligence and the impact on the labor market will be considered.

We are very pleased that we could win the network economist Dr. Holger Schmidt as a lecturer for this event!