Electives

Business analysts perform work for many different types of initiatives across an enterprise. The practice of business analysis is applied within the boundaries of a project or throughout enterprise evolution and continuous improvement. In this project-based module, the competencies, knowledge and skills needed for performing business analysis tasks will be acquired and used. A focus is on applying agile approaches and on exploring their advantages and disadvantages.

The objectives of the module are to enable the students to use special methods belonging to Artificial Intelligence (AI) - particularly nature-inspired methods, called Computational Intelligence (CI) - for solving and optimizing complex problems in business, computer science and engineering (including related disciplines such as robotics, computer games, etc.). The students learn about AI with a focus on CI as well as how to model, simulate and optimize problems on the computer. The following topics are particularly emphasized: Evolutionary Computation, Swarm Intelligence, Neural Networks, Fuzzy Logic, Meta-Heuristics, Robotics, and AI developments.

This module conveys Artificial Intelligence methods applied to concepts of drug discovery. It describes the drug discovery and development process and focuses in computational methods applied to select and identify small and large molecules to bring into clinics. They will be able to mine and analyze chemical and biological data. It provides practical know-how of applied machine learning to analyze and classify chemical and biological molecules for drug discovery. The module is offered by the School of Life Sciences; places are limited.

Business Analytics uses the increasing amount of available data to gain insight into business problems and propose competitive solutions. Thus, the module deals with the use of quantitative methods to support managerial work. Evidence-based management must take into account the quality of data and the uncertainty in results and predictions. Students acquire knowledge and skills in statistical data collection and procurement, data preparation, analysis, modelling, prediction and simulation. The methods come from probability, simulation, exploratory and inferential statistics including multiple regression. The application areas range from supply to operations, marketing, strategy and competitiveness analysis. Students carry out hands-on exercises with up-to-date software and with business data.

This module aims at students who seek to be challenged by real-world cases from different areas, be it mergers & acquisitions, digitalization, turning companies around, managing change, coping with a crisis, digital transformation or another topic of general interest.
During the class, students diagnose the situation of a real case presented by a guest manager and develop a shared understanding of how to plan and implement the change. Finally, the real-case scenario presented by the guest manager compliments the students’ solutions.

Cloud Computing is gaining more and more importance in companies and today forms an essential part of the modernization of IT, which enables the digitalization of the company. The guiding principle of the module is to provide participants with the technical and management cloud skills of the future to help companies evaluate and use the cloud. The participants can thus play an important role in the transformation of IT.

As threats to cyber security become increasingly ominous, sophisticated and unpredictable, CEOs, CIOs and other decision makers must address the risks. Larger organizations must also manage complex networks of service providers and many of whom have access to customers, sensitive data and critical technology. Under these circumstances, many organizations struggle to maintain the continuous vigilance and end-to-end visibility across the entire service delivery chain that is essential to a viable cybersecurity strategy.
In this course, we examine key challenges of cyber security and how effectively address them with mechanisms recently claimed as "cyber resilience".

More and more companies are going to understand that insights out of their data are crucial for their business success. Some people say, data is the new oil in a digitalized economy. But how do we get insights from data? How do we discover the knowledge hidden in data? For this purpose, many different techniques and algorithms were developed. This module explores the prominent representatives from Artificial Intelligence and Machine Learning – including prominently the very popular neural networks. Students will understand how the algorithms work and how to adjust them in order to be able to apply them in practice. Students apply the algorithms on realistic data sets and will get knowledge about their strengths and weaknesses. This module includes exercises in the programming language R.

The module covers the history of the healthcare system and the current financial, social, technological and scientific impact of digital transformation. The informatic relations among the stakeholders, e.g., institutions and patients, will be illustrated through practical handling of large-scale data and design of digital processes. Concepts of drug discovery and development, medical devices and biomedical engineering, and personalized medicine. Students will understand the concepts, the challenges, and the opportunities of the current digital transformation in healthcare. They will apply informatic methods to analyze digital large-scale data generated by innovative technologies and evaluate the interventions undertaken to promote digital innovation of healthcare processes. The module is offered by the School of Life Sciences; places are limited.

Digitalisation is reorganising entire industries, transforming business models and processes through the availability of digital data, the intelligent automation of work, the connectivity of things (internet of things) and value chains, and the creation of digital interfaces for users and applications.

This module investigates how the digitalisation affects (business) information systems supporting business processes in an enterprise, how an ideal interaction of natural and artificial intelligence in an organisational environment can be achieved, and how cooperation and partnership among humans and technology can result in an adequate business process execution. This investigation will be realized by application, implementation and demonstration of real prototypical instantiations. The module is organised as a project covering the whole life-cycle of business process management.

E-Business and Mobile Business build the core pillars of digital transformation. The E-Business perspective highlights the various impacts of inter-organisational information systems on strategies and value chains. The two views of e-commerce and e-procurement include topics like fulfilment services, personalisation, multichannel, direct to consumer (D2C), digital platforms, atalogue-based e-procurement and B2B integration. Mobile Business specifically addresses the growing significance of mobile business ecosystems in the digital economy. It analyses the economic benefit and impact, e.g. of networks and augmented reality. Case studies show how the concepts and theory are applied in practical situations.

This project-based module aims to conceive an innovative idea that has a significant impact in the environment of companies. The idea should lead to a business opportunity, a new business model or to developments with the potential of disrupting current business models. Students will learn how to apply innovation processes like Design Thinking to shape their ideas into sounded concepts. Students are expected to conduct an exhaustive research about both the target market and an up-to-date state of technological, social and psychological knowledge.

Field trips to Silicon Valley, Asia and South Africa open up opportunities for developing a global mindset. Understanding other countries’ economic, social, political and cultural systems and imprints is key. During the field trips the students have the opportunity to talk with managers of various companies and visit universities.The field trips to Silicon Valley and China have a special focus on innovation; the field trip to South Africa deals primarily with diversity.

To run a business efficiently requires a coordinated strategic and operational approach. Various standards, frameworks and so-called "best practices" offer recommendations for action on a variety of topics and, not least, on dealing with regulatory requirements that have to be mapped in an entrepreneurial context. The course focuses on strategic and operational methods and is organized in four interrelated themes - with a particular focus on the needs of digitization and information technology: (1) compliance, (2) risk identification and assessment, (3) governance and (a) Audit . An important and dedicated topic of the course is data privacy compliance with the new European Data Protection Regulation (GDPR), its impact on business processes and the required data management. The practical part of this course will be the application of a selected software solution for the operationalization and auditing of Internal Control Systems (ICS). Using this software, participants can select and compile reference models and standards and schedule and execute related audits.

Knowledge workers need experience and knowledge at different levels for their work and decision making, e.g. automatically derive and suggest possible solutions to the current problem. Supporting such tasks requires modelling and enacting several different forms of knowledge. In Artificial Intelligence several representation formalismen including rules and fuzzy logic are developed, which allow automated reasoning in order to support the human being. After completion of this module, the participants will be able to assess which kind of knowledge representation and reasoning is adequate and are able to develop appropriate knowledge-based systems.

Most entrepreneurs go about things differently. Their natural inclination is to put thinking into immediate action to see if it works. Lean entrepreneurship emphasizes developing an understanding of entrepreneurial thought, mindset, and action, and then progresses through idea generation, and screening for patterns to predict success, and which underlie entrepreneurial decision making for enterprise creation and growth.

The module covers personalized medicine and applies machine learning methods to understand, diagnose, and treat disease in individuals. It illustrates biostatistics and of various aspects of healthcare, from diagnosis, to treatment and mobile coaching, to end-of-life care. It teaches machine learning algorithms to analyze chemical and biomedical data in medicine. The module is offered by the School of Life Sciences; places are limited.

The objective of the module is to give a sound basis of IT management theories and practices. It also describes the main challenges concerning the digital transformation. Especially the role of cloud services in the enterprise as an enabler for the digitalisation is emphasised. The students get knowledge and understanding how to steer and develop the IT organisation in the enterprise in order to meet strategic objectives, to deploy the best tactical approaches and to assure the availability of IT systems at the operational level. The biggest challenge remains the leverage of the IT investments within an agile environment combined with quality and compliance service requirements, which most of the time leads to hybrid solutions.

Decision-making is based on data and knowledge. Decision-making (DM) processes are concerned with analytical approaches that help business actors in turning data into knowledge and action. Knowledge management (KM) processes are concerned with identification, storage, sharing, and effectively using knowledge, which can be explicit or implicit requiring different methods for managing it. The module explores decision-making and knowledge management processes that are driven by qualitative data and the required analytical approaches to exploit insight and sensemaking.

A focus of the module is on knowledge-supported decision making which requires knowledge. As several people and roles are involved in the decision-making, it is a challenge that decisions in an enterprise are consistent - independent of the individual person. Another challenge is that decision criteria are adapted to changing situations. This is the reason to combine decision-making and knowledge management in a single module.

This module is about the transformation of Supply Chain Management (SCM) to value co-creation in Networks. It is built around value co-creation with suppliers, internally, and with customers, as well as current supply chain technology, applications and research. It covers the fundamental concepts, methods and instruments of Supply Chain Management in purchasing, operations & distribution, and distributions. It gears students towards building a future of Value Co-creation in Networks with connectivity, singularity, ubiquity, and circularity.

Electives

Degree Programmes