Modules SS 2020

  • Artificial Intelligence and Deep Learning covers the basics of artificial intelligence and deep learning and recent technological trends. The course covers five primary topics:Fundamentals of artificial intelligenceFundamentals of deep learning, network design, and trainingConvolutional neural networks, illustrated through image recognitionRecurrent neural networks, illustrated through text miningDeep reinforcement learning - Learning to play games and beyond: Google’s AlphaGo
BPM and Organisational Practice explores Business Process Management (BPM) through an organisational-studies lens, so it is a BPM elective. Emphasizing the duality of stability and change in organisational work, the course covers the factors, mechanisms, and interventions that affect how processes behave over time. The course covers six primary topics:

  • Organisation theory
  • Process- and practice-based research
  • Organisational routines
  • Intra-organisational dynamics and endogenous change
  • Organisational learning, unlearning, and forgetting
  • The role of agency and intention in the execution of organisational work
Data Science covers statistical and exploratory techniques that are used to make sense of the vast and complex data sets that have emerged in business. Data Science is one of the core topics of the degree programme, so the course also provides a basis on which students can choose their electives. Students learn to detect patterns in large data sets in quantitative and qualitative formats to translate them into actionable insights. The course covers seven primary topics:

  • Data visualisation and exploration
  • Supervised learning techniques for regression (e.g. logistic regression)
  • Supervised learning techniques for classification (e.g. classification trees)
  • Unsupervised learning techniques (e.g. clustering, dimensionality reduction)
  • Fundamentals of deep learning
  • Text mining (e.g. topic modelling)
  • Hands-on labs with Python
In Digital Business, students collaborate with small and medium-sized companies to develop new business models, open new markets, and innovate with existing products and services, so students learn to recognise, understand, develop, and exploit digital innovations. The course topics change from semester to semester, but the course usually addresses seven grand themes:

  • Designing digital business strategy
  • Digital entrepreneurship and intrapreneurship
  • Opportunity recognition
  • Business model innovation
  • Value creation and cocreation
  • Digital transformation
  • Project management
Digital Humanities stands at the intersection between digital technology and social action – between computing and humanities. Besides enabling digital innovation, digital technology has fundamentally changed the way we see the world, work, and socialise. We are increasingly challenged to make sense of data and information, and turn them into things we can use for different goals. On the other hand, we also need to adjust ourselves in order to collaborate with each other through digital technology – and sometimes even with digital technology itself. How far should we go? How do we find a balance? This course is primarily concerned with understanding different and sometimes contradicting views on the relationship between digital technology and social action. The course covers five primary topics:

  • Introduction to digital humanities
  • The computational turn
  • Favourable views on digitization and digitalization
  • Critical views on digitization and digitalization
  • Examples of digital humanities projects
Digital Innovation covers the fundamentals of digital innovation and the development and implementation of novel and original solutions in which the innovation process, its outcomes, or the ensuing organisational and social transformation is embodied in or enabled by digital technologies. Digital Innovation is one of the core topics of
the degree programme, so the course also provides a basis on which students can choose their electives. The course covers six primary topics:

  • Fundamental properties of digital technologies and digital innovation
  • Organising for digital innovation
  • Digital platforms and ecosystems
  • Digital innovation and capital creation
  • Digital business models
  • Digital entrepreneurship
The Educational Journey covers lectures at a foreign university, company visits, and leisure activities. Course topics change from semester to semester.
Today, virtually all large organizations have to cope with growing complexity in their enterprise architectures (EA), which often comprise several hundreds or even thousands of IT applications that support an increasing variety of business processes. The underlying software components run on several generations of IT infrastructure, and digitization leads to increased intensity in inter-organizational interfaces and customer-centric solutions. As a consequence, EA comprises not only the fundamental structure and dependencies of business processes, IT applications, software components, IT infrastructure, and data in an enterprise, but also connected components of business ecosystem partners and customers. Changing only one of these EA components can impact a potentially large number of related components. Simultaneously changing several of these components in a number of change projects or transformation programs leads to potentially redundant (i.e. inefficient) and/or inconsistent processes, software systems, and/or IT infrastructure components. The short-term consequence is a waste of resources, and the longer-term consequences are increased effort and difficulty in maintaining existing information systems (because of excessive complexity) and shortage of resources that can be used for innovation.

EA management (EAM) is a management discipline that guides EA’s design and evolution. The goals of EAM are to control complexity, reduce inconsistencies, and leverage synergies in EA. EAM also supports the implementation of business innovation from a holistic perspective.
This course covers EA and EAM, incorporating both research findings and current examples from business practice. The course covers four primary topics:

  • Core concepts and the necessity of EAM
  • EAM use cases
  • EA modelling and analysis
  • Continuous improvement and maturity of EAM
Information Systems Development provides an introduction to programming including web frameworks that can be used in online environments such as e-commerce platforms or blog systems. The course covers six primary topics:

  • Introduction to scripting / programming
  • Software / programme development
  • Web technologies and web development
  • Web applications and their frameworks
  • Programming using existing frameworks
  • Project: Web platform
Information Systems Modelling focuses on systems analysis and design. In particular, the course covers methods of and approaches to modelling information systems in organisations. The course covers five primary topics:

  • Introduction to object-oriented systems
  • Project planning and initiation
  • Requirements analysis (i.e. requirements gathering and structuring)
  • Information systems modelling (i.e. UML modelling languages)
  • Information systems documentation
Network and System Security covers advanced security mechanisms in computer networks and systems and attacks against information systems. The course focuses on eight primary topics:

  • Essential network-security protocols
  • Attacks against common network protocols
  • Security issues in web applications
  • Security mechanisms in operating systems
  • Advanced exploitation techniques
Short description
The course focuses on developing research proposals in the field of data science.

  • Conducting literature reviews
  • Developing research questions
  • Designing qualitative, quantitative, and design oriented research
  • Writing research proposals
  • Ethical issues in data science