Study Modules

The module provides a deep dive into the field of software development. Basic programming skills are expected as a pre-requisite. We will dive into the world of Python programming and quickly recap the basic programming concepts such as variables, control structures, and functions. We will then move on to peek into object-oriented programming and from there move to Django, a web development framework for Python. Finally, well discuss agile development methods, clean code, open source development, version control, and some software engineering basics. To better understand the process behind software development, the first coding camp places students into a team software development project in which they get to understand and experience it. Students will be tasked with scoping, planning, and developing (coding) a small project, thus enabling an understanding of the challenges provided with all of these phases. This module is mandatory in all M.Sc. and MBA study programs. The content in all programs is identical. The workload in the hands-on projects is reduced for the MBA students to reflect the lower ECTS points.

The module provides a deep dive into the field of software development. Basic programming skills are expected as a pre-requisite. We will dive into the world of Python programming and quickly recap the basic programming concepts such as variables, control structures, and functions. We will then move on to peek into object-oriented programming and from there move to Django, a web development framework for Python. Finally, we will discuss agile development methods, clean code, open source development, version control, and some software engineering basics. To better understand the process behind software development, the first coding camp places students into a team software development project in which they get to understand and experience it. Students will be tasked with scoping, planning, and developing (coding) a small project, thus enabling an understanding of the challenges provided with all of these phases. This module is mandatory in all M.Sc. and MBA study programs. The content in all programs is identical. The workload in the hands-on projects is reduced for the MBA students to reflect the lower ECTS points.

In the second deep dive for coding, students are challenged to understand digital image processing and working with interactive devices, such as cameras or microphones. Discussed topics will be coordinate systems, color modes, the history of human-computer interfaces, vector vs. pixel graphics, computer vision, etc. To deepen the understanding, the students will also look into the necessary maths, e.g. matrix manipulations, etc. The basics of Object-Oriented Programming as discussed in Coding Camp 1 will be re-capitulated and deepened. To get started quickly and be able to work on interesting projects soon, we will use tools and libraries, such as Processing and OpenFrameworks. The programming languages of these tools are a subset of the Java programming language and C++. Both will be introduced in the module, always with a hands-on focus. In this second coding camp, students expand on the knowledge from the first coding camp: Knowledge and experiences of the first Coding Camp, such as project management and software development principles can be reiterated and students can experience further methods. The module is compulsory in all M.Sc. and MBA study programs. Contents are the same, the students in the M.Sc. programs have to create additional deep dives to certain course topics (more details in the assessment section). This is the description for the module in the MBA programs. As all German UDS modules, there are two weeks previous to Week 1 for the students to prepare for the module and two weeks after Week 8 to wrap up and reflect the course.

In the second deep dive for coding, students are challenged to understand digital image processing and working with interactive devices, such as cameras or microphones. Discussed topics will be coordinate systems, color modes, the history of human-computer interfaces, vector vs. pixel graphics, computer vision, etc. To deepen the understanding, the students will also look into the necessary maths, e.g. matrix manipulations, etc. The basics of Object-Oriented Programming as discussed in Coding Camp 1 will be re-capitulated and deepened. To get started quickly and be able to work on interesting projects soon, we will use tools and libraries, such as Processing and OpenFrameworks. The programming languages of these tools are a subset of the Java programming language and C++. Both will be introduced in the module, always with a hands-on focus. In this second coding camp, students expand on the knowledge from the first coding camp: Knowledge and experiences of the first Coding Camp, such as project management and software development principles can be reiterated and students can experience further methods. The module is compulsory in all M.Sc. and MBA study programs. Contents are the same, the students in the M.Sc. programs have to create additional deep dives to certain course topics (more details in the assessment section). This is the description for the module in the MBA programs. As all German UDS modules, there are two weeks previous to Week 1 for the students to prepare for the module and two weeks after Week 8 to wrap up and reflect the course.

In the second deep dive for coding, students are challenged to understand digital image processing and working with interactive devices, such as cameras or microphones. Discussed topics will be coordinate systems, color modes, the history of human-computer interfaces, vector vs. pixel graphics, computer vision, etc. To deepen the understanding, the students will also look into the necessary maths, e.g. matrix manipulations, etc. The basics of Object-Oriented Programming as discussed in Coding Camp 1 will be re-capitulated and deepened. To get started quickly and be able to work on interesting projects soon, we will use tools and libraries, such as Processing and OpenFrameworks. The programming languages of these tools are a subset of the Java programming language and C++. Both will be introduced in the module, always with a hands-on focus. In this second coding camp, students expand on the knowledge from the first coding camp: Knowledge and experiences of the first Coding Camp, such as project management and software development principles can be reiterated and students can experience further methods. The module is compulsory in all M.Sc. and MBA study programs. Contents are the same, the students in the M.Sc. programs have to create additional deep dives to certain course topics. More details in the assessment section. This is the description for the module in the M.Sc. programs. As all German UDS modules, there are two weeks previous to Week 1 for the students to prepare for the module and two weeks after Week 8 to wrap up and reflect the course.

This module develops a structured understanding of quantum software as a layered stack connecting physical hardware to high‑level applications. It begins by contrasting quantum and classical software paradigms, highlighting hybrid classical/quantum workflows and the implications of measurement, probabilistic behaviour and no‑cloning for software design. Building on this foundation, it introduces the quantum software stack (algorithms, circuits, SDKs, compilers, backends) using Qiskit as a reference framework, and compares local versus cloud execution as well as alternative platforms such as D‑Wave, Quandela and Pennylane. The module then deepens the view on simulators, noise models and hardware backends, including topology, error characteristics, embeddings and queueing, and explores hardware‑centric and application‑centric programming styles across frameworks. It concludes with application‑oriented development using Pennylane, integration of hybrid ML workflows and sound software‑engineering practices—modular architectures, testing, reproducibility and CI/CD—together with an outlook on current tools, specialized stacks and professional roles in quantum software.

This module provides a comprehensive introduction to macroeconomic principles, focusing on the behavior and performance of economies at a national and global level. Students will explore key topics such as economic growth, inflation, unemployment, fiscal and monetary policies, and the impact of international trade and globalization. The course emphasizes understanding how economic policies influence overall economic stability, development, and societal well-being. Through theoretical frameworks, real-world case studies, and data analysis, students will develop critical thinking skills and the ability to apply macroeconomic concepts to analyze economic issues and policy decisions. This module lays the foundation for informed decision-making in both public and private sectors.

Software systems and web applications are being used in more and more scenarios. As a result, these systems are becoming more complex, and the security of these software systems is becoming increasingly important.     This module focuses on methods and approaches for developing secure applications (e.g. secure coding and security by design). It also looks at different security measures for web applications, applications for smartphones / tablets and traditional applications. This module also covers various analysis methods that enable the identification and analysis of vulnerabilities and corresponding attack vectors at both theoretical and practical level. 

This eight-week module develops a coherent, cumulative understanding of how contemporary media systems are being re-architected by (i) artificial intelligence as a general-purpose capability layer, (ii) networked sensing and actuation through the Internet of Things (IoT) and home automation (domotics), and (iii) spatial-computing production pipelines (AR/VR/XR) that reconfigure how media environments are designed, rendered, composited, and experienced. The module then consolidates these technical and production-side foundations into a strategic, empirically oriented analysis of platform competitiveness, examining how AI reshapes competitive advantage across Microsoft, Amazon, Alphabet, and Meta—entities whose media-facing surfaces are simultaneously distribution channels, attention-allocation machines, and data-generating infrastructures. At its core, the module treats “AI in media” not as a discrete toolset but as an infrastructural reconfiguration of media production, distribution, and monetization: AI changes what can be produced (creative option space), how fast it can be produced (cycle time), how it can be found and reused (searchability and metadata), how it can be personalized and ranked (attention allocation), and how it can be measured and optimized (advertising and recommendation). This transformation is inseparable from governance constraints—privacy, cybersecurity, copyright, transparency, and competition policy—which are treated not as afterthoughts but as structural determinants of what is feasible, lawful, and legitimate at scale.

This module provides a comprehensive analysis of the regulatory frameworks governing artificial intelligence systems, with emphasis on compliance, risk management and strategic implementation in business contexts. The course covers the structure, scope and enforcement mechanisms of key AI regulations, particularly the EU AI Act, alongside intersections with data protection (GDPR), sector-specific rules and international approaches. Participants examine risk classifications, obligations for providers/deployers, governance requirements and ethical considerations through real-world cases in sectors like finance, healthcare and HR. Practical exercises focus on developing AI compliance strategies, conducting risk assessments and integrating regulatory demands into corporate decision-making.

This course provides the students with hands on experience solving a complex, yet limited problem in its scope. Instead of recognizing faces or fingerprints in an open population, the problem is solved for a limited population of individuals, for example, 100. The complete solution pipeline is developed, from data capture to data set generation and application of AI libraries in the cloud.

In this module the students apply AI libraries to large datasets managing a cloud system. Most large AI systems cannot be trained locally, due to the large size of the data bases. Students learn in this module how to load and manage Big Data systems, and how to create trainable systems for the cloud. In the course we look at the systems produced by Big Data companies for Data Warehousing, and experiment with one of them.

In this module the students apply AI libraries to large datasets managing a cloud system. Most large AI systems cannot be trained locally, due to the large size of the data bases. Students learn in this module how to load and manage Big Data systems, and how to create trainable systems for the cloud. In the course we look at the systems produced by Big Data companies for Data Warehousing, and experiment with one of them.

This module equips students with the theoretical foundations and technical skills to design and construct immersive virtual worlds, integrating the core systems of geometry, light, physics, rendering, and interaction. Emphasizing a synthesis of physical realism and interactive responsiveness, the course prepares students to build visually compelling, perceptually convincing, and functionally robust virtual worlds. Students will engage with topics including spatial modeling, coordinate transformations, lighting models, physical simulations, and real-time rendering pipelines, with practical implementation in professional XR development tools such as Unity. The course also addresses the optimization of performance, balancing aesthetic fidelity with technical constraints across XR platforms. Project-based work encourages students to iteratively build, test, and refine virtual environments where users can move, see, and interact fluidly.

This module builds an inductive map of how platforms and media businesses convert value creation into cash flow sustainably. Across cases, a recurring regularity is tiered access: firms start with broad reach, then carefully segment willingness to pay through freemium and paid levels, regional pricing, and packaging that trades limits, quality, and guarantees. Netflix, Disney+ and iQIYI illustrate canonical subscription ladders; Microsoft 365 combines seat based tiers with Azure metering; OpenAI pairs consumer and enterprise plans with usage based APIs; Springer Nature shows how contracted subscriptions and transformative deals stabilize revenue. A second regularity is bundling as a retention technology: Amazon Prime, Microsoft suites, Apple’s device linked services, Disney’s streaming plus experiences, and Comcast or Sky connectivity bundles raise willingness to pay, reduce churn, and enable cross subsidy. From these observations we infer a proposition: the best bundles anchor a high frequency utility core and attach emotional or aspirational complements. Weeks three to five generalize ecosystem dynamics. Content and intellectual property create a flywheel in which franchises are produced, distributed, monetized across formats, and reinvested, with Disney as the template and Netflix, WBD, Fox, and Tencent adapting it through global scale and rights. Yet pervasive multi homing weakens pure lock in; competition shifts toward differentiation in exclusivity, discovery, creator monetization, and bundle design. Complementors then become the scaling mechanism: developers, sellers, integrators, creators, and mini program builders expand variety and reduce marginal acquisition costs, as seen at Apple, Microsoft, Amazon, Google and Tencent. Finally, advertising auctions monetize attention through performance markets priced by clicks, actions, installs, leads, and views, while premium video inventory remains CPM oriented and increasingly programmatic. The module concludes with a predictive diagnosis: hybrids will dominate, mixing subscriptions, metered usage, bundles, ecosystem rents, and auctioned attention, with success hinging on coherent segmentation, incentive alignment, and reinvestment discipline.

The ongoing digitalization of society means that digital systems are becoming increasingly relevant and their protection is therefore becoming more and more important.     This module provides a general overview of cybersecurity, the state-of-the-art attacking and defending concepts and technologies, the basic knowledge on IT infrastructure, computer network, systems, and applications, as well as the CIA principles (Confidentiality, Integrity, and Availabilities) and common cybersecurity approaches (e.g., cryptography, firewall, antivirus, intrusion detection, etc).  

This module provides advanced knowledge about the structure and analysis of large amounts of data and how this is to be used in decision-making processes. Students learn the difference between descriptive, diagnostic, predictive and prescriptive analytics and their application in business contexts. In the module, theoretical concepts and approaches of objective analysis and decision-making are covered.

This module provides a comprehensive, practice‑oriented introduction to the legal and managerial frameworks that govern the collection, processing, sharing and monetization of data in organizations. It links core concepts of data protection, privacy and information governance with strategic decision‑making and corporate risk management in a global business environment. Students examine the main data protection regimes (in particular EU/UK GDPR‑style frameworks and emerging international approaches), governance models and accountability mechanisms, and apply them to realistic business scenarios and case studies. Emphasis is placed on designing compliant and effective governance structures, policies and controls that enable data‑driven innovation while safeguarding fundamental rights, organizational reputation and long‑term value creation.

Most advanced AI applications being developed and deployed today rely on one or more "Deep Learning" models. In this course, students will learn to construct deep neural networks, with or without attentional components. Students will train pre-configured networks using AI libraries and deploy them in the cloud. In the second part of the course, students will learn how to train ML models using reinforcement learning. The course as well will explore alternatives such as probabilistic networks and other types of graphical models. Recursive networks will also be covered.

Students will master fundamental leadership theories and digital transformation principles, developing competencies to lead hybrid and remote teams effectively. They will analyze digital leadership challenges, implement change management strategies for cultural transformation, and foster innovation in technology-driven environments. Through evidence-based frameworks and practical applications, students will acquire skills to navigate communication barriers, build virtual relationships, manage distributed teams, and drive organizational innovation. Upon completion, students will be equipped to lead confidently in digital contexts, applying contemporary leadership approaches to real-world challenges in increasingly connected organizations.

Students will master fundamental leadership theories and digital transformation principles, developing competencies to lead hybrid and remote teams effectively. They will analyze digital leadership challenges, implement change management strategies for cultural transformation, and foster innovation in technology-driven environments. Through evidence-based frameworks and practical applications, students will acquire skills to navigate communication barriers, build virtual relationships, manage distributed teams, and drive organizational innovation. Upon completion, students will be equipped to lead confidently in digital contexts, applying contemporary leadership approaches to real-world challenges in increasingly connected organizations.

Students will master advanced concepts for developing digital business models and creating new ventures in competitive digital markets. They will learn how to apply structured tools and methodologies throughout the venture creation process — from ideating business concepts to building minimal viable products and prototypes. The module equips students with competencies to design and implement digital value creation strategies for both start-ups and corporate ventures. Upon completion, students will be able to systematically develop, evaluate, and prototype digital business models that address customer needs while ensuring organizational competitiveness in digital transformation contexts.

Digital ecosystems and the platform economy are reshaping industries and redefining how value is created, delivered, and captured in the digital age. As platforms increasingly dominate markets — from e-commerce and mobility to finance and media — understanding their underlying dynamics is essential for future leaders. This module explores the transformative impact of digital ecosystems and platforms on the contemporary business landscape. Students will examine how these interconnected systems create value, reshape market dynamics, and challenge traditional business models.

This module provides a comprehensive introduction to the economics and principles of digital finance, bridging traditional finance with emerging fintech innovations. Students will explore the foundational concepts of corporate finance, financial markets, instruments, and institutions, with a particular focus on the frictions, inefficiencies, and challenges inherent in financial systems.  The module examines how digitalization, technology, and innovation are reshaping the financial sector — transforming investment and financing decisions and processes as well as financial intermediation. Students will develop a deep understanding of how technology reduces frictions, enables new business models, and create opportunities for innovation, while also considering the economic and regulatory implications of digital finance. By combining theory, practical case studies, and emerging trends, this module equips students with the analytical skills needed to evaluate, design, and implement fintech solutions effectively. 

Students will understand how digital transformation reshapes management practices and organizational structures through data-driven strategies. They will analyze human-AI collaboration, algorithmic management systems, and their impact on workers and workplace dynamics. Students will explore digital HR transformation, people analytics, and ethical challenges in digital organizations. Upon completion, they will be able to evaluate both benefits and risks of digital management, developing skills to lead responsible digital transformation that balances technological efficiency with human values and employee well-being.

Entrepreneurial finance and innovation have become critical drivers of sustainable growth and competitive advantage. To seize emerging opportunities and navigate uncertainty, future entrepreneurs and innovators must understand how to finance new ventures, evaluate risk, and strategically allocate resources. Strengthening financial acumen is essential for turning ideas into impactful, scalable solutions in dynamic markets. This module delves into the intersection of entrepreneurship, finance, and innovation, exploring how funding mechanisms and financial strategies are integral to the growth and success of innovative start-ups. Students will learn about the unique challenges and opportunities faced by entrepreneurial ventures in securing funding, and how these financial decisions influence their innovation trajectories.

This module examines hybrid media practice through applied, empirical case studies that illustrate the convergence of digital and analogue formats. Students integrate foundational design principles with contemporary production workflows, working across: • Adobe Creative Cloud (Photoshop, Illustrator, After Effects, Premiere Pro) for digital imaging, vector design, motion graphics, compositing, and post-production. • 3D and interactive toolsets (Blender, Cinema 4D, Unity, Unreal Engine) for modelling, animation, real-time rendering, and interactive development. • Web and UX/UI design (Figma; modern HTML/CSS/JavaScript prototyping frameworks) for user-centred design, iterative prototyping for web and mobile applications, and the implementation of interface design systems. • Integrated project development in film, animation, graphic design, and immersive AR/VR/XR—combining 3D assets, video, sound, and text into coherent, responsive compositions. • Creative coding and physical computing: programming interactive environments with Unity (a real-time 2D/3D creation platform); building sensor-driven, hardware–software interactions with Arduino (an open-source embedded platform); and developing web-based experiences with HTML, CSS, and JavaScript. More broadly, the module interrogates key themes in hybrid media—graphics, spatial and temporal composition, typography, interfaces, and sound—through concrete, illustrative case studies.

Covering the fundamental concepts, tools, and applications, this module aims to provide a comprehensive understanding of how these technologies create engaging and interactive experiences by blending the digital and physical worlds. Through a combination of lectures, hands-on labs, and project-based learning, students will explore the technical aspects of developing immersive content, including 3D modeling, real-time rendering, and user interaction. Additionally, the course will examine the impact of immersive technologies across various sectors such as education, healthcare, entertainment, and beyond, highlighting their potential to transform everyday experiences.

The goal of cybersecurity is to identify cyber risks and reduce them to an acceptable level. From a strategic view, an organization’s cyber-security program and cyber risk management has to fulfill five core functions. They have to be processes to identify cyber risks, a deployment of safeguards and detection capabilities, as well as organizational and technical measures to respond and recover from a cyber incident.  The module provides students with an overview and understanding of the principles of information security management that are commonly used in industry. It introduces widely used cybersecurity standards, frameworks, and methods. It explores critically the suitability and appropriateness of these standards, frameworks and methods for addressing challenges on today's organizational security requirements.

This module provides the conceptual and practical foundations to design, lead and evaluate innovation in public administration. It combines public‑sector innovation theories, dynamic capabilities, innovation units/labs, systems change approaches and experimentation with public‑value‑oriented impact measurement to enable participants to build and steer innovation portfolios in administrations.

This module develops the leadership capabilities needed to steer transformation towards impact of public administrations under conditions of political accountability, legal constraints and societal expectations. It combines ethical leadership, creative governance and accountability with change management in bureaucracies, stakeholder and citizen engagement, agile vs. hierarchical structures and crisis management to enable impactful, legitimate and resilient transformation programs.

This module is an introduction to logic, symbolic AI and the logic programming paradigm. It covers formal basics from logic and discrete mathematics, the fundamental principles and algorithms behind symbolic artificial intelligence, clausal logic, logic programming in Prolog and the resolution proof calculus. The students are enabled to solve classic symbolic AI tasks such as problem solving and game playing independently.

Decision-making is empowered by (big) data through the use of machine learning and data analytics principles. The course looks at subsymbolic systems: regression models, linear and nonlinear discriminators, decision trees, small neural networks, and support vector machines, among others This module conveys fundamental technologies behind big data applications. The students are tasked with un-derstanding and experiencing core principles of e.g. data harmonization and data pipelines fueling machine-learning algorithms. In the course, students will compare different theoretical approaches to AI and be able to choose the best problem-solving strategy for a given application.

This module explores how multiple sensory channels and sensor technologies can be combined to create advanced and immersive user experiences. Students will learn the scientific foundations and practical methods for integrating visual, auditory, haptic, and other forms of feedback with real-time sensor data, including from wearable devices and environmental detectors. The course covers key topics including sensor fusion, multisensory perception, and user experience design. Through hands-on projects and research-based approaches, students will develop skills to design, implement, and evaluate interactive systems that synchronise multisensor inputs and multimodal feedback. Applications include virtual and augmented reality, adaptive user interfaces, and robotics, preparing students to innovate in the field of interactive technologies.

This module examines how law and regulation respond to the rise of powerful digital platforms such as search engines, app stores, social networks, marketplaces and app-based intermediaries. It connects platform business models and multi‑sided markets with emerging regulatory regimes and enforcement practice in key jurisdictions (in particular EU, UK and US). Students analyze the main regulatory instruments applicable to platforms (competition law, ex‑ante platform regulation such as the EU Digital Markets Act and Digital Services Act, consumer and data protection, media and telecom rules) and explore their interplay. The module is designed for future managers and in‑house counsel who must navigate complex platform ecosystems, manage regulatory risk and engage with regulators and policymakers.

Within fast changing environments, a strategic perspective is fundamentally important for setting the right directions for future developments of companies. Therefore, the central aim of this module is to provide students with the economic understanding and skills necessary to become good strategists — whether in a large corporation, a mid-sized company, or an entrepreneurial startup. The module makes participants familiar with the economic foundations of strategic management, the role of entrepreneurs within firms and the economy, and various disciplines of strategic management, such as technology strategy, pricing strategy, or investment strategy. It covers strategic management on the business as well as on the corporate level and the entrepreneurial transformation following a good strategy process by analyzing case studies from various industries and regions.

Within fast changing environments, a strategic perspective is fundamentally important for setting the right directions for future developments of companies. Therefore, the central aim of this module is to provide students with the economic understanding and skills necessary to become good strategists — whether in a large corporation, a mid-sized company, or an entrepreneurial start-up. The module makes participants familiar with the economic foundations of strategic management, the role of entrepreneurs within firms and the economy, and various disciplines of strategic management, such as technology strategy, pricing strategy, or investment strategy. It covers strategic management on the business as well as on the corporate level and the entrepreneurial transformation following a good strategy process by analyzing case studies from various industries and regions.

This module is part of the “Rootcamp” which an increasing number of attacks are attempting to compromise individual systems or networked infrastructures. This module first looks at the relevant characteristics of different systems and networks in order to identify and categorize attack vectors and potential vulnerabilities. This then makes it possible to consider various theoretical security concepts and measures and to examine their practical implementation for specific attack vectors. In addition to the security concepts used and corresponding vulnerabilities of "classic" computer systems and networks, this module also deals with the security functions and potential vulnerabilities of systems - such as smartphones, IoT devices and cloud infrastructures - as well as emerging technologies for modern telecommunication - such as 6G.

This module is part of the “Rootcamp” which an increasing number of attacks are attempting to compromise individual systems or networked infrastructures.     This module first looks at the relevant characteristics of different systems and networks in order to identify and categorize attack vectors and potential vulnerabilities. This then makes it possible to consider various theoretical security concepts and measures and to examine their practical implementation for specific attack vectors. In addition to the security concepts used and corresponding vulnerabilities of "classic" computer systems and networks, this module also deals with the security functions and potential vulnerabilities of systems - such as smartphones, IoT devices and cloud infrastructures - as well as emerging technologies for modern telecommunication - such as 6G. 

This module explores how bureaucracies can become sites of purposeful, creative and ethical transformation rather than purely rule‑bound organizations. It integrates classic and contemporary theories of bureaucracy with concepts such as positive bureaucracy, creativity in organizations, mission‑driven governance and the “Yes, if” culture of creative bureaucracies, and links them to historical and international case studies of administrative reform and innovation.

In a digital world, the application of digital capabilities to processes, products and assets to enhance efficiency, increase customer value, manage risk and navigate through new revenue generation opportunities is key for a company´s success. The module will provide an advanced understanding of the role digital technologies play in today´s and the future business environment as well as its impact on national economy as well as societies. The main focus of the module will be on designing specific application scenarios of digital technologies across industries and for the advancement of the public sector. Therefore, the module builds on case studies from around the world and provides students with a holistic view on digital technology application and leadership-related aspects in this field.

In a digital world, the application of digital capabilities to processes, products and assets to enhance effi-ciency, increase customer value, manage risk and navigate through new revenue generation opportuni-ties is key for a company´s success. The module will provide an advanced understanding of the role digital technologies play in today´s and the future business environment as well as its impact on national economy as well as societies. The main focus of the module will be on designing specific application scenarios of digital technologies across industries and for the advancement of the pub-lic sector. Therefore, the module builds on case stud-ies from around the world and provides students a holistic view on digital technology application and leadership-related aspects in this field.

This module introduces quantum algorithms from foundational concepts to application oriented use cases. It begins with a recap of relevant classical algorithms and contrasts fault tolerant architectures with NISQ devices to clarify practical hardware constraints. Core primitives such as amplitude and phase estimation are developed and linked to Grover’s search, Quantum Fourier Transform and eigen value based algorithms. The module then addresses NISQ era methods, including variational and hybrid quantum–classical workflows, QAOA for combinatorial optimization, and quantum inspired approaches such as tensor networks. It concludes with an overview of quantum machine learning (including quantum neural networks, support vector machines and generative models) and a discussion of quantum advantage and utility, emphasizing realistic application scenarios and open questions.

This module teaches the mathematical foundations of quantum computing: Complex numbers, linear algebra (tensor products, hermitian and unitary operators), modular arithmetic, and matrix exponentiation.  The focus is always on the respective algorithmic and physical applications and background in quantum computing (Grover and Shor algorithms, quantum phase estimation, postulates of quantum mechanics, and density matrix with no communications theorem).

This module introduces the principles and objectives of cryptography, including fundamental terminology, classical encryption methods, and basic attack models. It examines perfect security through the One-time Pad and highlights its practical limitations. The module covers asymmetric cryptography and public-key infrastructures as solutions to the key exchange problem, while addressing emerging threats posed by quantum computing. Solutions like post-quantum cryptography are mentioned. The Quantum Key Distribution security paradigm is explored, grounded in core quantum principles such as measurement disturbance and the no-cloning theorem, with the BB84 protocol serving as a primary example. Students will learn how secure keys are established through post- processing steps including error correction and privacy amplification. The module further introduces entanglement and Bell inequalities, particularly the CHSH inequality, as the foundation for device-independent cryptographic protocols that ensure security even when the hardware cannot be fully trusted.

This module introduces quantum simulation as a central application of quantum computing. The course covers the theoretical foundations of quantum computation and Hamiltonian dynamics, key quantum algorithms for simulation, and the simulation of different physical systems. Students gain hands-on experience with variational ground-state algorithms, quantum chemistry and lattice models, and learn how noise, decoherence, and error mitigation affect practical simulations on near-term quantum hardware. Advanced topics include open quantum systems and comparisons between quantum simulators and tensor- network methods, enabling students to critically assess the capabilities and limitations of current and future quantum simulation approaches.

The group challenge is a fundamental part of the study program to apply learned concepts and frameworks and to build up additional competencies required for leaders in the digital world. The module poses a variety of challenges to a group of at least three students that commonly work on solving the given task. Challenges posed are individual per group but all focus on different aspects of digital trans-formation. This can include application scenarios in different industries or for the advancement of societies alike. Students in this module will be mentored by the professor and the teaching team to solve the challenge and thereby also learn and apply tools of digital project management.

The group challenge is a fundamental part of the study program to apply learned concepts and frameworks and to build additional competencies required for working in the field of quantum computing. The module presents a variety of technical challenges to groups of at least three students, who work collaboratively to solve a given task. Challenges are assigned per group, with all challenges focusing on different aspects of quantum computing and quantum information processing. This may include quantum algorithms, quantum simulation, hybrid quantum–classical workflows, or application scenarios across science and industry.

The institutional challenge advances the learnings from the group challenge is a central part of the study pro-gram to apply learned concepts and frameworks and to build up additional competencies required for leaders in the digital world in practice. The module poses a variety of challenges to group of approximately five students that commonly work on solving the given task. The challenges are provided by different companies and institutions, focusing on actual problems in their organizations related to digital transformation. Students in this module will be mentored by the professor and the teaching team to solve the challenge and thereby also learn and apply tools of digital project management.

The institutional challenge builds on the learnings from the group challenge and is a central part of the study program to apply learned concepts and frameworks and to develop additional competencies required for working in the field of quantum computing in practice. The module presents a variety of challenges to groups of approximately five students, who work collaboratively to solve a given task. The challenges are provided by different companies and institutions and focus on real-world problems related to quantum computing and emerging quantum technologies within their organizations. Students in this module are mentored by the professor and the teaching team while solving the challenge and, in the process, learn and apply quantum computing project tools and methods.

This module introduces students to the world of quantum computing. They will learn about the two computational models (circuit model with quantum gates as well as quantum annealing with quadratic unconstraint binary optimization problems (QUBOs)) and practice analyzing them using simple examples.  The module also covers the essential historical background and the current state of quantum computing and the global quantum ecosystem. No prior knowledge of mathematics or physics is required.

The group challenge is a fundamental part of the study program to apply learned concepts and frameworks and to build up additional competencies required for leaders in the digital world. The module poses a variety of challenges to groups of students that collaboratively work on solving the given task. Challenges posed are individual per group but all focus on different aspects of digital transformation. This can include application scenarios in different industries or for the advancement of societies alike.  Students in this module will be mentored by the professor and the teaching team to solve the challenge and thereby also learn and apply tools of digital project management. 

The Impact Project is a comprehensive (research-oriented) project that serves as the culmination of the MBA program. The central concept behind the Impact Project is choosing a specific problem and solving it with the knowledge the student has acquired during the studies. This problem shall be grounded in practical relevance for society, community or economy. The theme will be specified by the professor, who also shall be the supervisor. The students shall then work independently on a limited scientific and practical problem. The aim is that the students become acquainted with the scientific surroundings of their topic on the basis of relevant literature and develop their own solutions to the problem posed combining academic with practical relevance.

The Impact Project is a comprehensive (research-oriented) project that serves as the culmination of the MBA program. The central concept behind the Impact Project is choosing a specific problem and solving it with the knowledge the student has acquired during the studies. This problem shall be grounded in practical relevance for society, community or economy. The theme will be specified by the professor, who also shall be the supervisor. The students shall then work independently on a limited scientific and practical problem. The aim is that the students become acquainted with the scientific surrounding of their topic on the basis of relevant literature and develop own solutions to the problem posed combining academic with practical relevance.

The Impact Project is a comprehensive (research-oriented) project that serves as the culmination of the MBA program. The central concept behind the Impact Project is choosing a specific problem and solving it with the knowledge the student has acquired during the studies. This problem shall be grounded in practical relevance for society, community or economy. The theme will be specified by the professor, who also shall be the supervisor. The students shall then work independently on a limited scientific and practical problem. The aim is that the students become acquainted with the scientific surrounding of their topic on the basis of relevant literature and develop own solutions to the problem posed combining academic with practical relevance.

The Master Thesis is a comprehensive research project that serves as the culmination of the Master’s program. It requires students to independently investigate a specific topic within their field, applying advanced theoretical and methodological approaches. The thesis involves the development of a research question, extensive literature review, data collection and analysis, the presentation of original findings, and the defense of the final results of the research to different audiences. It demonstrates the student's ability to conduct rigorous research, critically engage with scholarly work, and contribute to academic or practical knowledge in their discipline.

This module onboards students to the program, the teaching and learning methods.    Irrespective of the area of implementation, digitalization and digital transformation pose complex challenges. Often, problems are not well-defined and need to be tackled in diverse areas being aware of many interrelated elements. Therefore, the skill to solve complex problems belongs to a set of so-called “future skills”, which humans need to thrive in and design the digital age. The module also teaches the principles, techniques and processes of Design Thinking, a user-centric approach to solve wicked problems and to design innovations. 

This module is part of the “Rootcamp” which onboards students to the program, the teaching and learning methods. It teaches the mindsets, methods and practices of Design Thinking, a user-centric approach to generating innovations. Design Thinking combines tools and practices from the fields of design, engineering, management, and social sciences. Design Thinking tools enable teams to ascertain user needs, generate innovative ideas for solutions, as well as to prototype, test and iterate these innovations. This user-orientation is combined with the perspective of technological feasibility and economic viability. A team-based approach, Design Thinking not only leverages the creativity and resourcefulness of individuals, but also enables collaboration and cooperation. 

This module onboards students to the program, the teaching and learning methods. Irrespective of the area of implementation, digitalization and digital transformation pose complex challenges. Often, problems are not well-defined and need to be tackled in diverse areas being aware of many interrelated elements. Therefore, the skill to solve complex problems belongs to a set of so-called “future skills”, which humans need to thrive in and design the digital age. The module also teaches the principles, techniques and processes of Design Thinking, a user-centric approach to solve wicked problems and to design innovations.

Students will master fundamental leadership theories and digital transformation principles, developing competencies to lead hybrid and remote teams effectively. They will analyze digital leadership challenges, implement change management strategies for cultural transformation, and foster innovation in technology-driven environments. Through evidence-based frameworks and practical applications, students will acquire skills to navigate communication barriers, build virtual relationships, manage distributed teams, and drive organizational innovation. Upon completion, students will be equipped to lead confidently in digital contexts, applying contemporary leadership approaches to real-world challenges in increasingly connected organizations.

This module explores how digital technologies enable sustainable investing, green finance, and financial inclusion. Students will learn to design fintech solutions that address ESG goals, support impact investing, and create measurable social value.  The module bridges finance, innovation, and sustainability, equipping students with frameworks to evaluate the financial, technological, and societal aspects of sustainable fintech solutions. 

The module offers an in-depth exploration into sophisticated modeling methods used in the creation of highly detailed and complex 3D objects and environments. It covers advanced topics such as sculpting, texturing, and shading, alongside procedural and parametric modeling techniques that allow for the creation of intricate patterns and forms not achievable through traditional modeling methods. The course emphasizes practical application in industries such as film, animation, video games, and virtual reality. Through hands-on projects, students will master the use of leading 3D software tools, enabling them to produce professional-quality models with efficiency and creative expression.

In this module, the students learn how to interpret, modify and create new deep learning architectures. We look at the different kinds of networking, activation functions and shortcuts, developing a classification of architectural principles that can be used for new projects. One important aspect is also understanding how to train networks and simplify them later, using self-learning principles.

This module deals with the ethics of AI in different do-mains. First the existing legislation is compared, using the USA, the European Union and China, as the reference cases. The course advances by considering the effect of AI systems in the justice domain, the urban case, in the financial markets, and the health providers. We review the on-going discussion, discuss dystopian and utopian scenarios, and derive conclusions for the designer of AI systems.

This module deals with the ethics of AI in different do-mains. First the existing legislation is compared, using the USA, the European Union and China, as the reference cases. The course advances by considering the effect of AI systems in the justice domain, the urban case, in the financial markets, and the health providers. We review the on-going discussion, discuss dystopian and utopian scenarios, and derive conclusions for the designer of AI systems.

Ever larger and more diverse data sets, such as event data, threat intelligence and open-source intelligence, are relevant for detecting attacks and potential risks in the context of cybersecurity. The challenge is to use ap-propriate techniques and concepts of AI technologies so that the relevant data can be analyzed efficiently and comprehensively. This module covers all the necessary steps, which in-clude collecting the data, normalizing and processing the data, the corresponding analytical methods and con-cepts and the visualization of the results. This module teaches the basic concepts and methods of AI and their application in the domain of cybersecurity, such as data exploration, streaming, ETL (extract, transform, load), correlation, supervised learning and unsupervised learning, emerging AI techniques, such as federated learning, active learning and Large Language Models (LLMs), etc.

This module introduces concepts, use cases and governance of AI, data and analytics in public administration, from data-driven policy and predictive analytics to generative AI and algorithmic decision support. Participants learn to identify and evaluate AI use cases, collaborate effectively with technical teams and understand regulatory and ethical boundaries for AI in the public sector, closely connecting to AI-regulation and data-ethics debates.

This module addresses the critical intersection of artificial intelligence strategy and responsible technology deployment. Students learn to develop comprehensive AI strategies that balance business value creation with ethical considerations, regulatory requirements, and societal impact. The module covers both the opportunities and risks associated with AI implementation, emphasizing the importance of governance frameworks, transparency, and accountability in AI-driven organizations.

The module provides conceptual and practical competencies to systematically understand, activate, and retain audiences in digital environments. Students explore strategies for audience engagement, data-driven segmentation, and the design of personalized content and experience strategies across multiple digital touchpoints. They learn to develop user profiles and audience journeys, design suitable content and interaction formats, and evaluate impact and value creation using appropriate metrics and analytics.

The module explores the intersection of technology and human capability enhancement. It delves into the latest advancements in wearables, biohacking, neurotechnology, and physical augmentation devices designed to enhance cognitive and physical performance. The course covers theoretical foundations, ethical considerations, and practical applications of augmenting human abilities through technology. Students will examine case studies on the impact of augmentation technologies in sports, work productivity, health, and disability. Emphasis is placed on the design, development, and deployment of technologies that safely and ethically enhance human performance, preparing students to innovate in the field of human augmentation.

This module enables participants to design and improve public services in close cooperation with citizens and stakeholders. It focuses on design thinking, citizen journeys and participatory formats to create inclusive, accessible and effective public services.

In this module students learn the classical computer vision algorithms for image processing, such as contrast enhancing, edge detection, color processing, feature detection, and program them for combination with an AI library. The focus of the second part of the module lies in dissecting current subsymbolic models in order to understand their inner workings. Students apply modern computer vision libraries, understanding the internal algorithms be-ing used.

The "Consumer Protection in E-Commerce" module (5 ECTS) in a university MBA "Digital Law" program equips students with legal frameworks safeguarding buyers in online transactions. It emphasizes EU and international regulations amid rising digital marketplaces. This module covers consumer rights in e-commerce, including unfair commercial practices, distance selling directives (e.g., Consumer Rights Directive 2011/83/EU), and digital content liability. Key topics include withdrawal rights, defective digital goods, misleading advertising, and platform accountability under the Digital Services Act (DSA). It analyzes case studies on dark patterns, subscription traps, and cross-border disputes, relating to FinTec Law through payment protections in digital finance. Recommended readings for the "Consumer Protection in E-Commerce" module draw from EU directives, OECD guidelines, and academic texts to cover regulatory frameworks and practical applications.

This module enables participants to understand and manage key cyber risks, compliance requirements and governance structures in digitally transforming public administrations. It connects cybersecurity, privacy and regulatory duties with innovation projects, so that digital government initiatives are secure, compliant and trustworthy by design.

This module provides advanced knowledge about the structure and analysis of large amounts of data and how this is to be used in decision-making processes. Students learn the difference between descriptive, diagnostic, predictive and prescriptive analytics and their application in business contexts. In the module, theoretical concepts and approaches of objective analysis and decision-making are covered.

This module provides an advanced survey of quantum algorithms and quantum machine learning with a focus on open research questions and rigorous evaluation. It begins by situating key resource models and advantage scenarios, then extends beyond basic QAOA to constrained variants, counter‑diabatic and warm‑start strategies, mixer design and parameter‑transfer techniques. Building on this, it develops a theoretical understanding of quantum kernels and variational models, including inductive bias, effective dimension, generalization, noise robustness and expressivity–trainability trade‑offs. Generative QML is treated in depth through QCBM, QGAN and QBM architectures, emphasizing training objectives, stability techniques, evaluation metrics and low‑tomography methods under realistic noise and shot constraints. The module concludes with the design and critical discussion of research proposals and proof‑of‑concept studies, supported by reproducible experimentation and systematic ablation analyses.

Students will master advanced concepts for developing digital business models and creating new ventures in competitive digital markets. They will learn to apply structured tools and methodologies throughout the venture creation process — from ideating business concepts to building minimal viable products and prototypes. The module equips students with competencies to design and implement digital value creation strategies for both start-ups and corporate ventures. Upon completion, students will be able to systematically develop, evaluate, and prototype digital business models that address customer needs while ensuring organizational competitiveness in digital transformation contexts.

Digital ecosystems and the platform economy are reshaping industries and redefining how value is created, delivered, and captured in the digital age. As platforms increasingly dominate markets — from e-commerce and mobility to finance and media — understanding their underlying dynamics is essential for future leaders. This module explores the transformative impact of digital ecosystems and platforms on the contemporary business landscape. Students will examine how these interconnected systems create value, reshape market dynamics, and challenge traditional business models.

Digital ecosystems and the platform economy are reshaping industries and redefining how value is created, delivered, and captured in the digital age. As platforms increasingly dominate markets — from e-commerce and mobility to finance and media — understanding their underlying dynamics is essential for future leaders. This module explores the transformative impact of digital ecosystems and platforms on the contemporary business landscape. Students will examine how these interconnected systems create value, reshape market dynamics, and challenge traditional business models.

This module provides a deep understanding of financial markets and instruments, with a focus on how digitalization and fintech innovations transform market microstructure, trading dynamics, and risk management. Students will explore traditional and digital financial instruments, market microstructure, and the mechanisms that govern liquidity, price formation, and trading efficiency.  The module examines the evolution of financial markets from conventional trading floors to high-frequency, digital, and decentralized markets, highlighting the impact of fintech on transaction costs, transparency, and accessibility. Students will learn to assess risks associated with digital financial instruments and develop strategies to manage them effectively from the perspective of investors and traders. By integrating theory with real-world fintech applications, this module equips students with the tools to understand and navigate modern financial markets. 

This module examines how organizations design governance structures, decision-making processes, and organizational architectures for the digital age. Students explore the tension between traditional hierarchies and agile, decentralized models, learning to design organizations that balance control with flexibility, speed with stability, and autonomy with alignment.

Across every strand of this module, from privacy regimes and security controls to copyright systems, platform rules, and AI ethics, one regularity emerges: digital value scales through data and content flows, and digital harm scales through those same flows when accountability lags. The pivotal point is therefore operational: compliance cannot remain a periodic legal exercise; it must become a living control system, designed into products, workflows, and infrastructure. Automation, continuous monitoring, and named control owners are the mechanisms that let governance keep pace with release cycles and vendor ecosystems, across jurisdictions, audiences, and monetization models. When teams translate obligations into a traceable chain of requirements, risks, controls, and evidence, abstract rules such as GDPR, PCI DSS, treaty-based rights, and fair use limits become enforceable guardrails: consent and retention logic, access governance, resilient backups and recovery, rights clearance, notice and action, and audit-ready logs. This integration also separates legality from legitimacy, because Corporate Digital Responsibility extends scrutiny to bias, manipulation, recommender systems, and synthetic media. Inductively, the module supports a predictive proposition: organizations that embed privacy, rights, and ethics by design will reduce breaches and infringement while earning durable trust; organizations that treat governance as paperwork will accumulate compounding operational, reputational, and regulatory failure.

Students will understand how digital transformation reshapes management practices and organizational structures through data-driven strategies. They will analyze human-AI collaboration, algorithmic management systems, and their impact on workers and workplace dynamics. Students will explore digital HR transformation, people analytics, and ethical challenges in digital organizations. Upon completion, they will be able to evaluate both benefits and risks of digital management, developing skills to lead responsible digital transformation that balances technological efficiency with human values and employee well-being.

This module focuses on advanced tools and frameworks for effective marketing and media activities within firms. Although the traditional marketing approaches and strategies are still required and used, companies across all industries continue to shift their focus to digital approaches including search engines, social media and metaverse technology. These areas take into account the journey of the customer and how they make their purchase decisions. Therefore, it is important for marketers to have an understanding of digital marketing strategies and familiarize themselves with the key technologies underlying them. This module offers an advanced view on digital marketing and media and provides insights into key strategies using Internet-based platforms. In addition, it will focus on content that resonates with consumers that helps businesses differentiate themselves in competitive mar-kets.

The module Digital Marketing focuses on basic tools and frameworks for effective marketing activities within firms. Although the traditional marketing approaches and strategies are still required and used, companies across all industries continue to shift their focus to digital approaches including search engines, social media and metaverse technology. These areas take into account the journey of the customer and how they make their purchase decisions. Therefore, it is important for marketers to have an understanding of digital marketing strategies and familiarize themselves with the key technologies underlying them. This module offers panoramic view of digital marketing and provides insights into key strategies using Internet-based platforms. In addition, it will focus on content that resonates with consumers that helps businesses differentiate themselves in competitive markets.

While private organizations often have more tangible drivers – growth, profit, market share – to push their digital transformation, governments and public services also need to transform because of their purpose. They need to ensure the well-being and advancement of their citizens and the country as a whole. Public services need to be accessible to everyone while ensuring data security and privacy. Pubic digital literacy or ownership of public data are additional aspects to consider when ad-dressing this topic.

While private organizations often have more tangible drivers – growth, profit, market share – to push their digital transformation, governments and public services also need to transform because of their purpose. They need to ensure the well-being and advancement of their citizens and the country as a whole. Public services need to be accessible to everyone while ensuring data security and privacy. Pubic digital literacy or ownership of public data are additional aspects to consider when ad-dressing this topic.

This module focuses on the legal and regulatory framework governing digital and cross‑border online business, with a strong managerial and compliance orientation. The module introduces participants to the key legal principles, regulations, and governance mechanisms that shape B2C and B2B e‑commerce at national, EU and international level. It covers contract formation online, platform and intermediary liability, consumer and data protection, competition and platform regulation, online payments and cybersecurity, as well as enforcement and dispute resolution in cross‑border digital trade. Case studies and practical exercises enable students to translate legal requirements into concrete risk‑management and compliance processes in digital business models.

Emerging technologies are transforming financial markets and creating new opportunities for innovation. This module advances students’ knowledge and understanding of fintech innovations, including blockchain, decentralized finance (DeFi), cryptocurrencies, tokenization, and smart contract platforms.  Students will explore the economic, technological, and regulatory implications of current innovations, evaluating their potential to reshape financial markets, enhance financial inclusion, and enable new business models. Through academic papers, case studies, and practical exercises, students will develop the skills to critically analyze emerging fintech technologies and assess their application in entrepreneurial ventures. 

Enterprise security, also known as corporate or business security, refers to the comprehensive set of strategies, processes, technologies, and policies that organizations implement to safeguard their assets, data, personnel, and operations from various security threats. The primary goal of enterprise security is to protect the organization's information, infrastructure, and resources while ensuring the continuity of business operations. This module explores the security requirements and practices of not only global companies but also small and middle-sized enterprises (SME).

Entrepreneurial finance and innovation have become critical drivers of sustainable growth and competitive advantage. To seize emerging opportunities and navigate uncertainty, future entrepreneurs and innovators must understand how to finance new ventures, evaluate risk, and strategically allocate resources. Strengthening financial acumen is essential for turning ideas into impactful, scalable solutions in dynamic markets. This module delves into the intersection of entrepreneurship, finance, and innovation, exploring how funding mechanisms and financial strategies are integral to the growth and success of innovative start-ups. Students will learn about the unique challenges and opportunities faced by entrepreneurial ventures in securing funding, and how these financial decisions influence their innovation trajectories.

Entrepreneurial finance and innovation have become critical drivers of sustainable growth and competitive advantage. To seize emerging opportunities and navigate uncertainty, future entrepreneurs and innovators must understand how to finance new ventures, evaluate risk, and strategically allocate resources. Strengthening financial acumen is essential for turning ideas into impactful, scalable solutions in dynamic markets. This module delves into the intersection of entrepreneurship, finance, and innovation, exploring how funding mechanisms and financial strategies are integral to the growth and success of innovative start-ups. Students will learn about the unique challenges and opportunities faced by entrepreneurial ventures in securing funding, and how these financial decisions influence their innovation trajectories.

In this module students learn to interpret the results produced by an AI classifier or AI generator. In the first third of the course the participants learn the classical statistical methods for determining confidence intervals, and variable sensitivity. In the second and third part modern approaches to explainability are dealed with: sensitivity analysis, relevance propagation, LIME, and others. The students will program an AI system with explainability component.

The "FinTec Law" module focuses on the legal and regulatory frameworks governing financial technology innovations. FinTec Law integrates financial regulation with broader digital law themes, serving as a specialized module in MBA Digital Law programs that builds on foundational digital topics while connecting to advanced ones like data privacy and AI governance.​ This module examines the intersection of law and FinTech, covering topics like blockchain, cryptocurrencies, decentralized finance (DeFi), smart contracts, regulatory sandboxes, data privacy in financial services, and AI-driven robo-advisory. It addresses regulatory challenges from EU directives (e.g., MiCA for crypto assets) and global standards, including tensions between innovation and compliance in digital payments, crowdfunding, and central bank digital currencies. Students analyze real-world case studies on disruptive technologies and their impact on traditional banking. FinTec Law overlaps with Data Protection and Privacy modules, as FinTech relies on GDPR-compliant data handling for payments, AI analytics, and blockchain transactions. It also links to Cybersecurity Law, addressing risks in decentralized ledgers and smart contracts common in financial innovations. These intersections emphasize compliance in digital ecosystems where finance meets technology.​

The FinTech Lab is a hands-on, research-driven module where students explore entrepreneurial opportunities in fintech. Combining academic research, market analysis, and product experimentation, students identify a fintech problem, develop a viable solution, and validate it through a structured venture-building process.  This module emphasizes research, critical thinking, and experimentation, allowing students to develop and test business models, analyze market trends, and design fintech solutions with both financial and technological rigor. 

This module introduces students to common algorithms used in financial markets in a playful way. The students learn about the mechanisms of the stock market by creating games that are implementing these algorithms. The game itself is mostly a vehicle to understand and apply these algorithms in a profound way. Students will first learn about the basics of game design and game theory. They'll then design an early game prototype that already sets the necessary game mechanisms and can be played without the knowledge about the financial algorithms, e.g. using random approaches such as dice, etc. Then the students learn about actual financial algorithms and in the following implement them in their game design by replacing the random approaches. Tey first do that for an analog game and later for a digital version of the game. Finally, the students compare and evaluate different approaches, collect their findings and present the results to the other participants in the form of a product pitch.

This module explores the evolving relationship between humans and artificial intelligence in business contexts, focusing on how AI can augment human capabilities rather than simply replace them. Students learn to design effective human-AI collaboration models, understand the organizational and psychological factors that influence adoption, and develop strategies for maximizing the complementary strengths of both humans and machines. The module emphasizes practical approaches for integrating AI into workflows while maintaining human agency and expertise.

To ensure the security of data and systems, it is necessary to ensure that only authorized people or systems have access to the relevant resources. In the context of cybersecurity, the Identity Management deals with the holistic view of different approaches and methods that can be used to meet this requirement. This module focuses on theoretical concepts and methods that can be used for authentication and authorization, and access control. In addition, approaches are taught that allow the different strengths and weak-nesses of each method to be identified. A further focus of this module is the consideration of various practical application scenarios in which the previously explained approaches are used, for example Kerberos, SAML and OAuth. Recent advances in this area, e.g., blockchain, decentralized identity management, behavioral authentication, will be introduced.

Across the module, observations converge on a regularity: disinformation scales when origin, context, and accountability are opaque and when network incentives reward attention over accuracy. A provisional proposition follows: credibility is not a property of a message alone but of an end to end system spanning micro claims, meso communities, macro platforms, and meta governance. Campaigns exploit this system via fabricated journalism, context laundering, impersonation, synthetic evidence, memes, conspiracy ecosystems, coordinated inauthentic behavior, microtargeting, data voids, and algorithmic exposure such as filter bubbles. A second, predictive proposition is that the most consequential threats will be hybrid, blending AI generated articles and deepfakes with bot amplification, market rumors, and regulatory trade offs where speech, security, and innovation collide. The course therefore treats verification as infrastructure. IFCN grounded fact checking, with transparent methods and corrections, is strengthened by AI tools for claim detection, media forensics, and provenance, including structured metadata, “nutrition labels,” and cryptographic attestations. Information architecture supplies the bridge: content models, taxonomies, evidence pathways to primary sources, and versioned updates make reasoning auditable. TIAV and TIVA then frame trust as calibrated interaction, aligning claim evidence, provenance, interface, governance, and feedback, and extending integrity verification into devices and software. The payoff is resilience, not mere persuasion.

This module provides an overview of international trends, frameworks and best practices in digital government and public-sector innovation. It enables participants to benchmark their own administrative context, understand OECD and EU orientations, and adapt international experiences to local transformation projects.

The Internet is a global network of interconnected networks and systems that communicate with each other using standardized protocols, which allows for the exchange of information among users worldwide. Due to its inherent design principles and open architecture, Internet based services and applications, especially the widely used web applications, suffer from huge number of threats and attack vectors. This module gives a detailed introduction on problems, especially security-relevant issues, concerning Internet and world wide web (www). The weaknesses and targets of Internet are discussed in detail with the focus on vulnerabilities and attack vectors of underlying internet protocols. The module also opens up the discussion on possibilities to detect attacks and intrusions.

This module equips students with the knowledge and skills to anticipate future technological developments and manage technology strategically within organizations. Students learn to identify emerging technologies, assess their potential impact, and develop foresight capabilities to navigate uncertainty. The module combines strategic thinking with technology management principles, enabling students to make informed decisions about technology investments and innovation pathways in dynamic business environments. 

This module conceptualizes media innovation and sustainability not as parallel agendas but as a mutually constitutive relationship: contemporary media systems—through their technologies, infrastructures, institutional arrangements, and narrative power—both shape the conditions of sustainable development and are themselves increasingly constrained by sustainability imperatives. Anchored in the United Nations Sustainable Development Goals (SDGs) as an overarching normative horizon, the module investigates how media organizations and platform ecosystems can be redesigned so that innovation becomes a means of sustaining public value, rather than a synonym for novelty, acceleration, or market disruption alone. The module proceeds from a central premise: media sustainability is multidimensional. It cannot be reduced to financial survival, audience growth, or competitive advantage. Rather, it must be understood through four interlocking pillars: 1. Environmental sustainability: the ecological footprint of media production, distribution, storage, and consumption (e.g., data centers, streaming, device lifecycles). 2. Social sustainability: media’s role in democracy, cohesion, inclusion, accountability, and resistance to disinformation and greenwashing. 3. Human sustainability: labor conditions, professional identities, newsroom culture, skills, well-being, and ethical agency in increasingly datafied environments. 4. Economic sustainability: durable, resilient value creation and capture, including governance models that protect editorial integrity. Across eight weeks, students move from foundational definitions and historical transitions (broadcast → platform ecosystems) to strategic design mechanisms (segmentation, personalization, cross-platform orchestration, participatory systems), then to critical media policy and economy (concentration, framing, power), academic perspectives (STS, innovation studies, critical media studies, environmental communication), and finally to global landmark cases spanning subscription entertainment, platform marketplaces, targeted advertising, consumer AI, real-time news, and decentralized digital infrastructure.

Media Platforms and Ecosystems interrogates digital media business as a distinctive managerial arena shaped by two sided markets, media clusters, and the conversion of information into cultural value and soft power. Week 1 develops the conceptual grammar and economic logic of the sector, connecting non rival public goods, high fixed and low marginal distribution costs, economies of scale, product risk, rapid innovation, and content repurposability to strategy and performance. Using end of December 2025 equity market evidence of a 149.55 trillion dollar public company universe, with 62.17 trillion dollars or 41.57 percent in media adjacent digital sectors, and using 2026 research and development allocation patterns, students trace how platforms, software, telecommunications, semiconductors, gaming, and artificial intelligence co evolve. Weeks 2 to 8 examine platform governance in closed and open ecosystems; user interaction through recommendation, user generated content, and gamification; data monetization through subscription and paywall designs; content repurposing; vendor lock in; long tail economics; and software versioning as a strategic lever. Students practice ecosystem mapping, value capture analysis, and argumentation. Case studies from Meta, Alphabet, Amazon, Microsoft, OpenAI, Apple, ByteDance, Tencent, Disney, Comcast, Warner Bros Discovery, BBC, Al Jazeera, and Netflix anchor analysis in comparative, region sensitive managerial decision making.

This module examines the legal and regulatory issues of virtual worlds, metaverse platforms and immersive VR/AR applications, focusing on governance, liability and rights in hybrid. Participants explore how existing legal frameworks in areas such as platform and content regulation, data protection, consumer and financial law, IP, labor and competition law apply to metaverse platforms and immersive VR/AR solutions, and where regulatory gaps arise. Special attention is given to questions of jurisdiction and applicable law in borderless virtual spaces, the contractual and governance structures of platforms (including DAOs), human‑rights concerns and the enforcement of rights against powerful providers that may act like “de facto mini‑states”. Through case studies on virtual goods, digital identity, virtual workspaces and entertainment, students translate abstract principles into practical risk‑management, contracting and compliance strategies for organizations operating in or with virtual worlds.

Mobile and wireless communications are nowadays pervasive in both our personal life and industry. Meanwhile the loosely coupled wireless interfaces offer an even bigger attack surface. The fast-paced innovation in this area makes it challenging for cybersecurity to keep up, while vulnerabilities on mobile and wireless applications become increasingly impactful. This module covers mobile and wireless security on both system and application layers. The state-of-the-art security concepts for wireless networking and mobile operating systems (both iOS and Android) and applications will be introduced. Specific security challenges (attacks) and their solutions on resource constraint Internet of Things (IoT) and edge computing scenarios will be discussed. In addition, security requirements, standards, and technologies for modern telecommunication network, e.g., 6G, will be covered as well in this module.

The field of natural language understanding has been profoundly transformed by the introduction of attention and sequential probabilistic models. In this module the student learns what are probabilistic models, how they can be implemented and how recursive solutions can be enhanced with attention components. The examples to be instrumented are completing and summarizing text, and question answering. The course also introduces the student to the use of statistical methods in speech synthesis and speech recognition systems.

While symbolic AI systems are based on logic, and sub-symbolic models are based on neural networks, probabilistic models induce an explicit probability distribution on the possible worlds of interest. In this module, the students learn how to structure probabilistic models, how to train them, and how they can be used. They also learn when probabilistic models can be used to assess the impact of outside interventions, and how to integrate them with relational logic to model complex application domains, as they occur for instance in the life sciences.

The module merges the principles of project leadership with the entrepreneurial strategies tailored for the digital reality market. It covers key project management methodologies, including agile and waterfall, adapted for VR, AR, and MR projects, emphasizing iterative development, stakeholder engagement, and effective communication. Concurrently, it addresses the entrepreneurial aspects of product ideation, market validation, business model innovation, and pitching to investors, all within the context of digital reality ventures. Students will learn to navigate the complexities of starting and managing digital reality projects, from conceptualization to market launch, ensuring they are well-equipped to lead in this rapidly evolving industry.

This module builds the financial and entrepreneurial capabilities needed to design, justify and implement innovation projects in public administrations. It connects public budgeting, business cases, cost‑benefit and public value analysis with entrepreneurial approaches and funding instruments, enabling participants to argue for and realize robust transformation initiatives.

This module focuses on how public administrations can use Public Private Partnerships (PPPs) to build and govern digital ecosystems and digital public infrastructure. Participants learn to structure PPPs with technology providers, allocate risks, and design collaboration models that support sustainable, trustworthy and innovation‑oriented digital services.

This module develops a structured understanding of how quantum technologies can be translated into viable business models. It starts by positioning quantum computing within digital transformation and reviewing core business concepts such as value creation and capture, stakeholders and the distinction between technology and business model innovation. Students learn to apply Business Model, Lean and Value Proposition Canvas to analyse technology‑driven firms and to design quantum‑enabled value propositions for selected industries. The module then maps the quantum ecosystem (hardware, cloud, software, research, start‑ups, regulators) and compares Quantum‑as‑a‑Service with on‑premise deployments along technical, economic and regulatory dimensions. It concludes with a discussion of quantum platforms and multi‑sided ecosystems, monetization and interoperability challenges, and the potential impact of quantum advantage on value chains,

This module introduces students to computational complexity theory, focusing particularly on the quantum complexity classes QMA and BQP. It covers the fundamental concepts of complexity classes, reductions, and hardness/completeness, and illustrates these with typical complexity problems. While students must be familiar with quantum computing, no prior knowledge of complexity theory is required.

This module provides an overview of the physical implementation of quantum technologies and their applications in data processing and sensor technology. The quantum mechanical fundamentals relevant to quantum computing are covered. The most important computational models, including quantum circuits and annealing paradigms, are presented. Leading quantum hardware platforms—such as trapped ions, NMR systems, superconducting circuits, photonic systems, neutral atoms, and solid-state defects—are discussed with a focus on the realization, control, gate operations, and measurement of qubits. Quantum annealing and adiabatic quantum computations are also covered, including their connection to optimization problems and comparisons with gate-based quantum computers. The final section explores quantum sensing technologies, highlighting how quantum interference and coherence enable high-precision measurements in applications such as atomic clocks, magnetometry, inertial sensing, and quantum imaging.

This module introduces the foundations of classical and quantum information theory, beginning with Shannon’s framework of information. The mathematical formalism of quantum systems, covering qubits, measurements, composite states, and entanglement is repeated. These concepts are extended to noisy quantum processes described through density matrices, fidelity measures, and quantum channels. Quantum entropy measures and quantum data compression provide a deeper understanding of information in quantum systems and the role of measurement. Building on this, the module explores entanglement as a resource for quantum communication, including dense coding, teleportation, purification, and entanglement swapping. The characterization and quantification of entanglement are examined. The module concludes with classical and quantum error correction and progressing to quantum error correction codes.

This module teaches the fundamentals and architecture of quantum networks and the quantum internet. It explains the essential quantum concepts underlying networked quantum information. In addition, it covers in detail the distribution of entanglement, quantum repeaters, and key protocols that enable quantum communication over long distances. The module covers quantum-based security, including quantum key distribution, and explores how entanglement enables distributed quantum computations, distributed gates, and advanced multi-party protocols. It also introduces delegated and verifiable quantum computations and concludes with the technological and theoretical requirements for building scalable, interoperable, and robust quantum internet infrastructures.

Classical AI systems are trained using special training data sets. The modern approach, in many domains, is to let the computer train itself using learning by reinforcement. In this module students learn the basics of RL systems and how they have been combined with deep learning models In the course we discuss the interplay of RL with generative AI and how they achieve synergy.

This module examines the legal, regulatory and ethical challenges of robotics and autonomous systems in business and society, with a strong focus on risk, liability and governance in concrete application domains. The module introduces participants to the main legal questions raised by industrial, service and social robots, autonomous vehicles, drones and human–machine interaction in both physical and virtual environments. It analyses how existing regimes in tort and product liability, contract, data protection, medical and transport law, as well as fundamental rights and safety regulation, apply to robotics and where new regulatory approaches are being developed. Learners work with case studies from sectors such as manufacturing, logistics, healthcare, mobility and care robotics, translating abstract legal requirements into operational policies, contracts and compliance processes.

This module provides a comprehensive exploration of creating software for immersive experiences such as virtual, augmented, and mixed realities. Focused on the full development lifecycle, it imparts essential programming skills, platform-specific development practices, and user interface design tailored to 3D environments. The course emphasizes hands-on learning through the construction of applications that leverage spatial computing, real-time 3D rendering, and user interaction. Students will also critically assess the implications of digital reality technologies on society and user privacy. By the end of the course, participants will be proficient in developing robust, user-centric digital reality software.

Across eight weeks, the module develops an inductive theory of how organizations create, defend, and renew value through strategic communication and corporate storytelling in hybrid, algorithmic contexts. It clarifies what makes communication strategic (purpose, audience, constraints) and what makes storytelling powerful (structured meaning linking evidence, emotion, and moral logic), then shows how integration strengthens persuasion, relationships, and legitimacy. Students build typological literacy: communication by intent (informational, persuasive, relational, legitimating), temporality, and control; channels via a control interaction matrix; narratives by form (classical plot, episodic fragments, transmedia worlds), medium (text, visual, data, immersive), and evidence regime (mythic, experiential, testimonial, scientific, coordinative). A co evolutionary value perspective distinguishes conjectured from realized value, diagnosing slippage, capture, and exchange value across financial, non financial, and time dimensions. This lens supports diagnosis, prediction, and redesign. The module reframes audience analysis from targets to interpretive publics and algorithmic publics, integrating demographic, psychographic, behavioral, and network models into strategic narrative development: define purpose, integrate insights, articulate tension, position protagonists, design value and evidence, calibrate voice, and test for coherence, resonance, credibility, and adaptability. It extends evaluation beyond applause metrics through narrative visualization and storytelling dashboards, and interrogates data storytelling and generative AI, emphasizing empirical effects, limits, and governance. Crisis weeks operationalize narrative under pressure through problem solving steps, core crisis types, SCCT aligned response strategies, and a ten step playbook. The module culminates in orchestrating media strategy narratives across convergence, spreadability, and transmedia power. Hypothesis: legitimacy and resilience grow when intent, audiences, channels, and evidence remain aligned.

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The module "Anti-Fraud & Compliance" (5 ECTS) provides an in-depth examination of preventive measures, detection techniques, and regulatory adherence against fraud in digital ecosystems, building directly on modules like FinTec Law and Consumer Protection in E-Commerce. This module explores anti-money laundering (AML) regulations, fraud typologies in digital transactions (e.g., phishing, identity theft, ransomware), and compliance under EU directives like the 6th AMLD and Digital Operational Resilience Act (DORA). It covers risk assessment tools, whistleblower protections, forensic auditing in blockchain/DeFi contexts, and corporate governance for ethical AI use in fraud detection. Case studies link it to prior modules like FinTec Law (payment fraud) and Consumer Protection in E-Commerce (online scams), emphasizing cross-border enforcement. The module is structured around three pillars: regulatory frameworks (e.g., EU's 6th AML Directive, DORA for ICT resilience, NIS2 for cybersecurity reporting), fraud typologies (phishing, deepfake scams, crypto laundering, ransomware in e-commerce), and compliance tools (KYC/AML software, AI anomaly detection, blockchain forensics). Weekly topics progress from foundational concepts—such as fraud triangles and red flags in digital transactions—to advanced applications like cross-border investigations under Europol guidelines and ethical AI deployment for transaction monitoring. Practical components include simulations of Suspicious Activity Reports (SARs), risk heatmaps for FinTech platforms, and audits linking consumer data breaches to financial crimes.