The goal of this course is to write the Bachelor Thesis on one of the multiple topics of business informatics or informatics.

• Introduction, Basics, Overview
• Data Models, Database Systems, Data Independence
• The Relational Model (Basics, Design)
• Relational Query Languages
• Relational Algebra
• SQL
• Conceptual Modelling
• UML2
• Object Diagram
• Class Diagram
• Dependency Theory and Relational Design Theory (Dependencies, Normal Forms)

• Number representation
• floating point arithmetic
• Basic concepts of information and coding theory
• logic in computer science
• Propositional logic, Boolean algebra, minimization methods
• Predicate logic as a specification language
• Finite automata, including Moore and Mealy automata
• Regular expressions and context-free grammars
  
• combinational circuits 
• Realizations of automata
  
• Petri nets

Introduction to science and the operation of the scientific community; based on a self-chosen or a given topic students practice developing a research question, performing a literature search, basic skills of scientific writing, and giving a scientific presentation

This course discusses in detail all phases of modern software development for large systems, including requirements elicitaton, design, implementation and validation. Specifically, the course covers:

• Modern software development models;
• Functional and non-functional requirements and their elicitation;
• Modeling and specification of software systems;
• System implementation aspects, such as design patterns, delta debugging, CI/CD, and code reviews;
• Software validation techniques, such as structural, functional, system, and user-acceptance testing.

Reliability issues in modern software often result in significant financial losses or system downtime, thereby affecting millions of users. This course discusses in detail fundamental techniques for ensuring the reliability of large, complex software systems. Such techniques are heavily used in practice and range from static program analysis and verification to automated test generation. The course, in particular, focuses on applications of these techniques to different, popular domains, such as smart contracts and machine-learning models.

Introduction to the interdisciplinary research field of business informatics

• design-based methods
• empirical-quantitative methods
• empirical-qualitative methods
• data-driven methods
• formal-analytical methods

The presentations by lecturers on the various research methods are as follows:

Science, technology and society are intertwined. Science and technology formed the foundation of our modern society and will play an even bigger part in a world with 9 to 11 billion people on this planet.  The pivotal role of science and technology in the development and advancement of our societies is undeniable. However, our livelihoods threatened by unintended consequences of technology.

Innovations such as artificial intelligence, automation and digitalisation will have profound impacts on all aspects of our lives, work, the way we govern our societies and conduct wars. Synthetic biology, nanotechnology, new materials and production technologies could fundamentally change the way we interact with the physical and biological world.

All of these technologies provide significant opportunities, but also threats.

In this lecture we will be discussing the mega trends that we should be mindful of, and how we could envision a positive future in which technology and science serve humanity. To fulfil that vision, what should be our contribution and our responsibility as future scientists and engineers, as managers and as members of society?

Finally, what do we expect from alumni of a technical university in the 21st century? Technical excellence is certainly required, however we should reach for more:

• critical thinking and assessment of the consequences of technology, especially in own field of work
• focusing on important and meaningful areas for society: are the best people working on the most important problems? what is your contribution? where do you contribute the most?
• ability to communicate own expertise and consequences of technology with non-experts, management and other stakeholder
• capability to lead, manage and motivate teams and co-workers even under very challenging conditions

Programming tasks in respect to the "Programmieren in Processing" MOOC

• Basics and definitions.

• Information systems, their applications, and their architecture

• The role of conceptual modeling in the (model-driven) engineering of information systems

• Conceptual domain model versus conceptual database model.

• Ontology-guided creation of conceptual models

• Stepwise transformation of conceptual domain models, via conceptual information (systems) models, towards implementation platforms, such as relational database management systems, business rule engines, ERP systems, and low-code platforms.