• Understand the motivation and concepts of virtualization as well as its limitations and disadvantages
• Understand the motivation and concepts of cloud computing as well as its limitations and disadvantages
• Know the latest technologies and services as well as their strength and weaknesses
• Explain the business rational behind the various concepts and technologies

• Be able to handle key technologies in the area of virtualization and cloud including their set-up and configuration
• Select the correct technologies for a given IT scenario and be able to explain the rationale behind
• Develop an architecture for an end-to-end solution using the selected technologies
• Implement and deliver a working end-to-end solution based on the architecture, the selected technologies as well as user applications

• Design and run experiments to explore the capabilities of virtualization and cloud solutions (e.g. quality of service)
• Be able to independently explore new functionalities and features of virtualization and cloud technologies and use them to create new solutions
• Be able to optimize the performance of virtualization and cloud computing solutions
• Develop a high-level business rational for virtualization and cloud solutions
• Work with an international team and deliver working virtualization and cloud solutions
• Create and communicate a convincing storyline for technology selection, architectures and business models

• Infrastructure as a Service
• Platform as a Service
• Software as a Service

• AWS & OpenStack
• Kubernetes
• Serverless Computing and Functions

• Network Virtualization
• Edge Computing

• Theoretical knowledge: combination of lectures and independent e-learning modules
• Practical Skills: several labs with design, implementation and test of virtualization and cloud infrastructure
• Scientific Competences: semester project including designing, running and analyzing experiments

• Understanding the role of innovation in the software development lifecycle, particularly in the context of digital transformation
• Mastering the stages and techniques of Design Thinking and in user-centered software design
• Gaining a deep understanding of Agile methodologies, including SCRUM and Kanban, and their relevance to iterative software development.
• Familiarity with essential tools for software development, including version control (Git), bug tracking systems, UML modeling, and Agile project management tools (e.g., Jira).
• Understanding DevOps principles, continuous integration/continuous delivery practices, and tools for automating software deployment and monitoring.
• Knowledge of emerging trends such as AI-driven development, cloud-native architectures, microservices, IoT, and blockchain technologies in the context of innovative software solutions.
• Understanding the key elements of successful pitches, including audience analysis, value propositions, and clear communication of technical solutions to non-technical stakeholders.

• Apply Design Thinking techniques to create and prototype software solutions that effectively address user needs and challenges
• Setup and manage a team based on agile principles
• Utilize software tools to manage collaborative development in team environments
• Create and interpret UML diagrams (use case, sequence, class diagrams, etc.) and other modeling tools for designing and communicating software architecture.
• Prototype cloud-native solutions using containers, microservices, and serverless architectures
• Adapt and integrate new and emerging technologies into software projects
• Develop and deliver compelling pitches for software innovations, tailored to various audiences, including investors, stakeholders, and users.

• Ability to think critically and apply innovative methodologies to design, develop, and refine software solutions that address complex, real-world problems
• Lead cross-functional teams in the development of software products that prioritize user needs
• Ability to work in interdisciplinary teams, integrating perspectives from design, business, and technology to drive software innovation and translate between different domains
• Apply Lean startup principles to turn software prototypes into viable products or business ventures, validating ideas, and scaling solutions in the market
• Competence in considering ethical, social, and environmental impacts of software solutions
• Practice communication strategies to clearly explain technical concepts, business value, and user benefits.

• Interactive lectures: Traditional lecture format enhanced with real-time discussion and interactive elements. If applicable, industry professionals, startup founders, or tech innovators deliver guest lectures with additional industry insights
• Groupwork: Collaborative projects where students work in interdisciplinary teams to prototype innovative software solutions
• Hands-on Workshops: Practical sessions where students apply tools and techniques discussed in class
• Self-Directed Learning and Research: Students explore specific areas of interest related to the course content through independent study and research
• Peer Reviews and Critique: Students provide constructive feedback on each other’s work during project development and pitch presentations

• MOD2-01 – Usability Engineering
• MOD-E03 – Human Centered Digitalization

• Understand the core issues of agile projects
• Know software development and deployment concepts and processes, such as DevOps and CI/CD
• Explain methods for user participation in the software development process
• Understand cooperation in virtual teams using collaboration tools
• Explain and compare methods for managing agile projects, especially Scrum and Kanban
• Explain and compare workflows and design flows for agile projects

• Conduct a software development project in an agile team, using Scrum in a virtual collaboration setting
• Apply tools for managing software development projects
• Develop tailored processes for managing software development projects
• Define team roles, especially Scrum Master and Product Owner
• Set up IT environments for collaboration in virtual teams

• Cooperate in a virtual team using online collaboration tools
• Develop an agile mindset
• Handle complexities while working in groups
• Present and defend team results in a complex virtual environment
• Develop team competencies among the members
• Perform successfully in an agile virtual team and accomplish tasks
• Reflect on team situations, address resulting issues, and find solutions
• Cooperate with a team of software developers from other Master’s programs and manage interdisciplinary work successfully
• Manage teams and projects in intercultural and international settings
• Compile findings and literature reviews into scientific papers on virtual team collaboration in agile cross-border projects

• Introduction to Agile Software Development (SW) Projects
• Refresher Course on Scrum
• Software Engineering Methodology, esp. DevOps, CI/CD
• User Centered Design

• Setting up the team and assigning the roles, especially Scrum Master and Product Owner (based on a Belbin Test for all team members and reflection on own team/project personality)
• Developing an idea for a mobile app (based on a selection of cases) and pitching of the idea and the project planning as a kick-off event.
• Conducting 2 months of (weekly) sprints, documentation and review of project artefacts
• Demonstration of a klick prototype and final project review

• Introduction to scientific methodology, especially literature reviews and paper writing
• Review and discussion of the recent research in the field, selection of topics for own paper
• Preparation of a scientific paper in group work (ca. 2 months)
• Peer review of the papers and assessment
• (if possible) submission to a scientific conference and presentation

• Lectures introducing concepts, methods and tools
• Project simulation (agile, virtual SW development projects with Scrum) on the case study of a mobile app development, in mixed teams with SW developers from another international Master’s programme. Several sprints are conducted over 2 months’ time. Review meetings with teachers and 2 reviews in the plenary.
• Group work on writing a scientific paper, peer review by students and teachers
• Presentations to communicate results

• Usability Engineering (MOD2-01)
• Requirements Engineering (MOD-E02)
• Managing Digital Change (MOD-E08)

• know research methods and tools of the digital transformation (scientific) domain
• know and understand the culture of different partner countries
• know programming languages and modelling techniques
• know web development techniques, languages, tools and frameworks
• have IT literacy in tools like MS Excel, Word and Powerpoint
• know German vocabulary and grammar at least on A1 level
• know English vocabulary and grammar at least on C1 level

• apply research methods and tools of the scientific domain
• work in international and intercultural settings
• can program software in Java (alternative: C# or Python)
• can model system in UML (or sysML)
• can develop basic web applications
• use tools like MS Excel, Word and Powerpoint proficiently
• speak, understand, read and write German at least on A1 level
• speak, understand, read and write English at least on C1 level

• Students can cooperate in a cross-border project with international students
• Students can adapt and to cope with different European cultures
• Students learn to communicate with people from different countries

• Students can plan and conduct scientific research in their field
• Students are aware of their own cultural background and can interact with other cultural background adequately

1. Intercultural Training (ICT): The intercultural training is intended to help the students to interact and work successfully with their teachers and peers at the university. It is conducted also as a team building event for the new class in the first semester. It should also motivate students for a later mobility/exchange with the partner universities.
2. Compact Web Development Course (online): This course delivers the basics of web programming languages and frameworks. It is intended for catch up for students with only very limited web development skills.
3. Compact Programming Course (Java, alternatives: C# or Python): This course delivers object-oriented programming skills in Java (decision is made prior to semester start, can be switched to C# or Python depending in the language used in the 1st semester). It is intended for catch up for students with limited programming skills.
4. Modeling of Software Systems (UML): This course delivers object-oriented modeling skills in UML. It is intended for catch up for students with limited software and systems engineering skills.
5. Research Methods and Tools – part A (RMT-A): Introduction to scientific methods and tools in the digital transformation domain. Furthermore, analysis of relevant scientific trends and communities. Students can prepare for scientific work via the sequence of RMT-A and RMT-B plus a Research Seminar.
6. Cross-Border Project A: During the November Master block week or a workshop at a partner university, projects with teams of students from several partners are formed. They conduct projects, e.g. on industry cases and present the results, e.g. in pitching.
7. ICDL-Excel: students who lack relevant IT skills can take part in the preparation courses for the International Computer Driver License (ICDL) at FH Dortmund and do the respective exams. The Excel course puts the focus on using Excel for data analytics and business intelligence.
8. International Project Communication 1 e (German A1): A language certificate of German at least on level A1 has to be provided at the end of the semester. Respective courses are organized and embedded into the weekly schedule.
9. International Project Communication 1 g (other language): For students with native German background (e.g. German/Austrian/Swiss citizens or students with a prior degree taught in German (e.g. “Bildungsinländer”), a language certificate in an additional language (e.g. French, Spanish, Chinese, etc.) at least on A1 level is required. In case of an English language certificate, C2 level is needed

1. Intercultural Training (ICT): lectures and role plays
2. Compact Web Development Course: online, set of LinkedIn courses with tests
3. Compact Programming Course: online courses, programming tasks with reviews
4. Modeling of Software Systems (UML): lectures, exercises and written exam  
5. Research Methods and Tools – part A (RMT-A): lecture  
6. Cross-Border Project A: project and presentation
7. ICDL Excel: methods & tool training
8. International Project Communication 1 e (German A1): language training
9. International Project Communication 1 g (other language A1 or English C2): language training

1. Intercultural Training (ICT): exam
2. Compact Web Development Course: online tests (LinkedIn)
3. Compact Programming Course: review of the programming tasks, related questions
4. Modeling of Software Systems (UML): written exam  
5. Research Methods and Tools – part A (RMT-A): homework (paper assignment)
6. Cross-Border Project A: presentation and discussion
7. ICDL Excel: test
8. International Project Communication 1 e (German A1): language test
9. International Project Communication 1 g (other language A1 or English C2): language test

• Analyze and differentiate between different architectures and central architectural patterns of web applications
• Name and categorize important web standards and technologies

• Derive and design a suitable architecture for solving a specific problem
• Determine and combine suitable web standards and technologies for implementing this architecture
• Use advanced web engineering tools, such as development environments, bundlers, scaffolding and transpilers

• Analyze a complex requirement and break it down into sub-requirements
• Implement an extensive task within the context of a project over several weeks
• Develop and implement solutions cooperatively in a team
• Present, explain and discuss their ideas and solutions

• Architectural patterns such as MVC and its variants (MVVM, MVP, etc.)
• Request-based and component-based backend web frameworks
• Single vs. multi page applications, server-side rendering, client-side rendering, hybrid approaches (e.g. rehydration, resumability)
• Reactive programming/streaming

• Online E-Learning materials with interactive slides and videos (asynchronous self-study)
• Interactive classroom sessions (on-premise) for tasks and exercises based on examples from practice and research (e.g. coding, group exercises, lightning talks), for additional in-depth content, and for answering and discussing questions

• MOD2-02 – Software-intensive Solutions
• MOD-E01 – Software Engineering Project

• Name relevant ITIL operational processes for the successful management of IT services including the management of underlying IT infrastructure
• Distinguish phases of the IT service lifecycle and to prioritize processes and practices relating to theses phases
• Focus on value creation in IT service delivery according to ITIL in context of typical enterprise settings
• Acquired expertise in implementing industry best practices and emerging innovations to drive automation, with a strong focus on developing reliable and efficient continuous delivery pipelines.

• Apply, design and implement operational processes for IT services in line with ITIL recommendations
• Manage and operate IT infrastructure while deploying, testing, and monitoring IT services using cloud-based environments

• Analyze a complex operational environment with respect to utility and warranty of the IT service delivery and the associated value creation
• Develop an improvement plan based on the findings of a previous ITIL-based process analysis
• Propose an organizational set-up for an ITIL-based operational environment
• Mastered advanced DevOps methodologies and deployment architectures, enabling the design and optimization of scalable, resilient, and high-performance technical solutions

• Compact Course on ITIL: Analysis of a case study and presentation of results.
• Deployment and DevOps: Analysis of deployment project solution and presentation of results.

• Passed compact course on ITIL
• Passed deployment project completion

• Smart Home & Smart Building & Smart City (MOD-E09)
• Edge Computing (MOD-E10)

• Agutter (2013): ITIL Lifecycle Essentials, IT Governance Publishing
• Axelos (2019): ITIL Foundation: ITIL 4 Edition, The Stationary Office Books
• Axelos (2011): ITIL Service Strategy, The Stationary Office Books
• Axelos (2011): ITIL Service Design, The Stationary Office Books
• Axelos (2011): ITIL Service Transition, The Stationary Office Books
• Axelos (2011): ITIL Service Operation, The Stationary Office Books
• J. Fitzgerald, M. Skelton, J. Kanies, and K. Bauer (2017).Effective DevOps: Building a Culture of Collaboration, Affinity, and Tooling at Scale. Sebastopol, CA, USA: O’Reilly Media
• G. Kim, J. Humble, P. Debois, and J. Willis (2021). The DevOps Handbook: How to Create World-Class Agility, Reliability, & Security in Technology Organizations, 2nd ed. Sebastopol, CA, USA: O’Reilly Media
• B. Beyer, C. Jones, J. Petoff, and N. R. Murphy, Eds. (2016). Site Reliability Engineering: How Google Runs Production Systems. Sebastopol, CA, USA: O’Reilly Media

• know advanced research methods and tools of the digital transformation (scientific) domain
• know and understand business models in the digital domain
• know TOGAF and enterprise IT & business architectures
• know training concepts
• have advanced IT literacy in tools like MS Excel
• know German vocabulary and grammar at least on A2 level
• know English vocabulary and grammar at least on C2 level

• apply research methods and tools of the scientific domain
• can develop business models based on case studies
• can develop enterprise IT architectures based on case studies
• can train users in IT tools
• use tools like MS Excel on an advanced level
• speak, understand, read and write German at least on A2 level
• speak, understand, read and write English at least on C2 level

• Students can cooperate in digital transformation projects
• Students can train users in digital technologies
• Students learn to communicate with people on different IT literacy levels
• Students learn to communicate in different languages, especially in German

• Students can plan and conduct scientific research in the digital transformation domain
• Students are aware of their own discipline and can interact with other discipline adequately
• Students can manage context beyond the IT technology domain

1. Compact Course on Business Models and Business Cases (TOPSIM): This course conducts a 1-week intensive workshop as a business simulation in the TOPSIM framework. The focus is on the development of a startup idea in the field of digital transformation.
2. Compact Course on TOGAF: This course conducts a 1-week intensive workshop on the TOGAF framework (The Open Group Architecture Framework). The focus is on the development of an enterprise architecture combining the business and the IT view.
3. Train-the-Trainer on IT tools for projects: The goal of the course is to let the IT students develop a training, starting from the training concept (didactics, learning objectives), then developing training materials, and finally delivering the training to students from a project management Master.
4. Research Methods and Tools – part B (RMT-B): Training on advanced scientific methods and tools in the digital transformation domain. The goal of the course is to prepare a concrete research project or a scientific publication. Students can continue the sequence of RMT-A and RMT-B plus a Research Seminar.
5. Cross-Border Project B: During the Mai Master block week or a workshop at a partner university, projects with teams of students from several partners are formed. They conduct projects, e.g. on industry cases and present the results, e.g. in pitching.
6. ICDL-Advanced Excel: This course is preparing for the Advanced Excel certificate of the International Computer Driver License (ICDL) and the respective exams. The course puts the focus on using Excel for data analytics and business intelligence.
7. International Project Communication 2 e (German A2): A language certificate of German at least on level A1 has to be provided at the end of the semester. Respective courses are organized and embedded into the weekly schedule.
8. International Project Communication 2 g (other language): For students with native German background (e.g. German/Austrian/Swiss citizens or students with a prior degree taught in German (e.g. “Bildungsinländer”), a language certificate in an additional language (e.g. French, Spanish, Chinese, etc.) at least on A1 level is required. In case of an English language certificate, C2 level is needed.

1. Compact Course on Business Models and Business Cases (TOPSIM): business simulation
2. Compact Course on TOGAF: online preparation, 1-week workshop based on case study
3. Train-the-Trainer on IT tools for projects: development of a training course (group work)  
4. Research Methods and Tools – part B (RMT-B): lecture and homework (paper writing)  
5. Cross-Border Project B: project and presentation
6. ICDL Advanced Excel: methods & tool training
7. International Project Communication 2 e (German A2): language training
8. International Project Communication 2 g (other language A1 or English C2): language training

1. Compact Course on Business Models and Business Cases (TOPSIM): pitch presentation
2. Compact Course on TOGAF: result presentation and review
3. Train-the-Trainer on IT tools for projects: evaluation of the training by participants  
4. Research Methods and Tools – part B (RMT-B): homework (paper assignment)
5. Cross-Border Project B: presentation and discussion
6. ICDL Advanced Excel: test
7. International Project Communication 2 e (German A2): language test
8. International Project Communication 2 g (other language A1 or English C2): language test

• Differentiate basic principles of software design.
• Differentiate, analyze, and apply key patterns at the macro- and micro-architecture level
• Know relevant tools and methods for domain-driven design
• Name and classify current research approaches to modeling software architectures

• Apply basic principles of software design to concrete application scenarios
• Select, combine and implement suitable methods for domain-driven design

• Analyze a complex problem and break it down into subproblems
• Implement an extensive task within the context of a project over several weeks
• Develop and implement solutions cooperatively in a team
• Select and apply appropriate methods for the interdisciplinary development of solutions, in particular together with domain experts without technical background
• Present, explain and discuss their ideas and solutions

1. Short repetition of the Bachelor material on software design (e.g. design patterns according to Gamma et al., Separation of Concerns, layered architecture)
2. In-depth aspects of software design:
   • Principles (e.g. loose coupling - high cohesion, SOLID)
   • Architecture patterns (e.g. ports and adapters, CQRS)
   • Methods (e.g. Domain-Driven Design, WAM approach)
3. Characteristics and patterns of modern architectural styles (e.g. modular architectures, event-based architectures, microservice architectures)
4. Model-driven design, development and reconstruction of software architectures

• Flipped/inverted classroom:
• Online E-Learning materials with interactive slides and videos (asynchronous self-study)
• Interactive classroom sessions (on-premise) for tasks and exercises based on examples from practice and research (e.g. coding, group exercises, lightning talks), for additional in-depth content, and for answering and discussing questions
• Lab project: Project task which is worked on in teams over the entire semester
• Guest lectures featuring experts and recent topics from research and industry

• MOD1-02 Software Architectures
• MOD1-03 Digital Systems 1

• Know relevant theoretical foundations of usability engineering
• Explain and compare established usability engineering tools and methods (AB-Tests, GOMS, Interviews, Usability-Lab Tests, Remote-Tests, etc.)
• Understand perception of and interaction with standard WIMP based user interfaces. the applicability of those tools and methods in a given project situation
• communicate concepts for different target groups (professional peers, user groups, management, etc.)

• Observe, recognize and evaluate user behavior and behavioral patterns (e.g. analyzing video protocols from user tests)
• Analyze context of use by empirical methods like field study or derive it from statistical usage data
• Derive requirements from the established context of use
• Create a prototype for a given set of requirements selecting and using an appropriate method (e.g. paper prototype, design prototype, interactive prototype)
• Evaluate a given prototype or (software) system selecting and using an appropriate method (e.g. cognitive walkthrough, heuristic evaluation, AB-test, informal methods, lab test)
• Adapt and improve those methods and tools for new application areas and interaction paradigms

• Guide a team through all steps of user centered development
• Create all necessary artifacts in a user centered design process
• Provide a self-reliant evaluation of the recent status of research in a (small) given area
• Develop communication concepts for new/adapted target groups
• Relate and evaluate the methods and tools into the recent scientific publications
• Critically reflect behavior (own and well as others) in general, as well as in a given situation

• Motivation
• Definition Usability Engineering

• Usability Engineering -Processes
• Integration into IT-projects
• Potential conflicts
• Communicating Usability

• Analyzing context of use
• Requirements management
• Concepts
• Evaluation

• Mobile Computing
• Individual software solutions
• Consumer- vs. Business-Software
• Industrial solutions

• E-learning modules and (live-)video lectures on usability engineering foundations
• Project work (e.g. as part of a block week) to learn practical skills and apply selected tools and methods
• Guest lectures with experts and trending topics (e.g. mini-lectures) as part of a block week
• Literature work and conducting (pre-)studies to improve scientific competences on usability engineering

• Innovation Driven Software Engineering (MOD1-01)
• R&D Project Management (MOD1-04)
• Scientific & Transversal Skills 1 (MOD1-05)

• can explain the design of digital ecosystems as a field of activity in industry
• can explain and contrast design patterns for business models of digital ecosystems
• can explain and contrast design patterns for the system structure of digital ecosystems

• identify and explain the the business model and the components for a given digital ecosystem
• identify and critically comment on ethical and social issues of given digital ecosystems
• plan and execute the design of a digital ecosystem as part of the construction process
• explain and apply systemic thinking as interdisciplinary and cross-organizational thinking

• critically comment on and discuss a given plan for shaping a digital ecosystem.
• critically comment on and discuss a given design for a digital ecosystem with regard to its design quality

• successfully contribute their own work results in an interdisciplinary exchange
• include the social dimension in the introduction and further development of digital ecosystems as part of the design process
• recognize and explain ethical and social dimensions as part of the design work of digital ecosystems

• Evolution of functionalities within the ecosystem
• Changes/extensions of the business model
• Expansion/reduction of the elements of an ecosystem

• Solution level (patterns for business models)
• System level (patterns for system structures: open vs. closed, hierarchical vs. heterarchical ecosystems, agent systems as patterns)

• Impact of digital ecosystems on existing sectors of the economy (example "click worker" and "supplier precariat")
• Sustainability issues relating to digital ecosystems (example: mail order)
• monopoly positions of powerful ecosystems (e.g. Amazon as a marketplace)

• theoretical principles and concepts are taught in interactive formats (e.g. Piazza technique) and deepened using given examples
• Methodological skills and practical application are taught and practiced using a self-chosen case study as a group project.
• Critical analysis and reflection on ecosystems is enhanced in the frame of project presentations and written assignments.

• Knows deep knowledge of formal verification methodologies
• Knows relevant theoretical background
• Knows, understands, and critically assesses specific system requirements

• Can apply advanced methods to novel and complex use cases
• Can designs and optimizes verification models and artefacts (e.g. properties)
• Can use and adapt UML approaches and tools (UPPAAL, TAPAAL) in innovative contexts

• Can research on state of the art and theoretical background
• Can present and critically discuss results in multidisciplinary teams
• Can structure and synthesize complex scientific fields to create new insights

• What are Formal Methods?
• Why should we use Formal Methods?
• When in the overall development process should we use Formal Methods?
• Model Checking
• Theorem Proving
• Testing
• Formal Verification in practice: The MechatronicUML Approach
• Recent Research: literature review
• AMALTHEA Methodology and Tool Chain

• Lectures, Labs (with MechatronicUML), homework
• Access to recent research papers
• Literature review and discussion of results
• Lectures, homework
• Group work
• Exercises or projects on the basis of practical examples
• project-oriented internship in teamwork
• Writing of a scientific paper

• MOD1-02 – Distributed and Parallel Systems
• MOD1-03 - Embedded Software Engineering
• MOD2-01 – Mechatronic Systems Engineering

• Know relevant theoretical foundations, area: computer science and society
• Explain methodical background of case studies and surveys
• Aware of critical limitations of methods for evaluating impact

• Analyze the impact of changes in information technology on individuals, environment and society, based upon a given past scenario
• Evaluate, analyze (and within limits predict) the impact of new products/services on individuals, environment and society, during the concept and development phase
• Conduct methodologically structured evaluations (e.g. field observation, lab tests) and surveys

• Discuss impacts of changes in information technology on individuals, environment and society with experts
• Advise during product/service development on potential impacts of product/service structure/fea- tures on individuals, environment and society
• Understand scientific publication in the related area

• Basic Overview “Computer Science & Society”
• Ethics in computer science
• Digital media and art
• Surveillance and privacy
• Artificial Intelligence and responsibility
• Case Studies “Disruptive Changes by Information Technology”
• Digitalization of work life & work environments, processes, products and services
• Evaluation of impacts (personal, environment, society)

• E-learning modules and (live-)video lectures on computer science and society
• Online self-learning material on evaluation methods in social sciences
• Project work (e.g. as part of a block week), for a case study (e.g. Analyzing impacts and potentials for news products and services)
• Guest lectures with experts and trending topics (e.g. mini-lectures) as part of a block week
• Literature work and conducting (pre-)studies to improve scientific competences

• Innovation Driven Software Engineering (MOD1-01)
• R&D Project Management (MOD1-04)
• Usability Engineering (MOD2-01)

• explain the basic characteristics of data and data collection
• explain advanced functionality of Python
• explain the core concepts of data analytics and business intelligence

• acquire data
• apply Python and libraries for data analytics
• use Python and libraries for machine learning

• students train to work in projects together with people from different cultural backgrounds
• in discussion students develop a critical attitude to data based decision making and to issues like privacy and data protection

• Project-based learning with supporting theoretical knowledge (video-)lectures introducing concepts, methods and tools, tool tutorials.
• Practical Skills: group work to practice concepts and methods, to develop skills and to work on case studies, feedback and consulting lectures
• Scientific Competences: presentations to communicate results and do a scientific discussion and reflection

• Knows concepts and architectures of real-time embedded systems
• Knows key aspects of real-time networking
• Has acquired overview of cloud computing and selected cloud platforms

• Can implement, deploy and test simple IoT-systems
• Can set-up and utilize a cloud system
• Can analyze the E2E latency in distributed systems

• Can design a simple IoT system for a given set of requirements
• Can structure an IoT development project regarding function and time
• Can propose and implement measures to reduce latency in a distributed system

1. Introduction
2. Real-time Embedded Systems
3. Real-Time Networking
4. Cloud Computing
5. Edge Computing

• E-learning modules and lectures on IoT and Edge Computing
• Small project with Eclipse IoT stack
• Access to the Open Edge Computing Initiative and the Living Edge Labs

• video lecture accompanying project work with final presentation
• Flip teaching (inverted classroom) is used
• completion of programming tasks on the computer, individually or in teams
• lab practice with KNime

• can explain the basics of the digital transformation in organizations
• can explain and compare digital business models
• know methods and tools for change management
• know the characteristics and specifics of digital change
• can explain the various aspects involved in setting up and running a company
• know maturity models and leadership concepts

• analyse and develop digital transformation projects
• apply change management to organizations
• design people development and trainings concepts for digital change
• develop tailored concepts for sustainable digital transformation

• develop and discuss concepts in teams
• support teams as change agent or technology steward
• communicate, facilitate and motivate digital change
• present the results to companies and discuss in a professional context

• foster and promote digital change
• develop an ethical sense towards digital change and an entrepreneurial mindset
• think strategically in an uncertain environment
• work in teams and set up a digital transformation project for the respective case study

•     Digital Transformation – Incremental Change & Disruption
•     Definitions & Characteristics of Digital Change

•     New Digitalized Forms of Management, Iterative & Incremental
•     Business Models and Business Relations in the Digital Era
•     Change Management (Lewin, Kotter …)
•     Digital Transformation of Organisations – Maturity Models
•     Chances and Risks of Digital Transformation in Organizations

•     Leadership in the Digital Age
•     Entrepreneurial Mindset, Culture & Ethics
•     Developing Competences, People and Teams
•     Change Agents & Technology Stewards

•     Strategy in the Digital Era - Scenario Based Strategy
•     Disruption
•     Lean (Startup)
•     Sustainable Digital Transformation – Impact & Responsibility

•     Change vs. Transhumanism vs. AI
•     Data Ethics
•     New Work based on Frithjof Bergman

• conduct a digital transformation project in an existing company or organisation with a focus on organisational change
• conduct a digital transformation project in an existing company or organisation with a focus on the digital transformation of a business model
• develop a start-up project with a focus on a new, disruptive digital product or service

• to write a business plan including financial planning.
• present a 90 second elevator pitch of the business idea
• perform a 15 minute pitch presentation to a fictional panel of potential investors

• based on a company case provided by industry expert
• own entrepreneurial startup project => work-integrated learning (WIL), challenge-based (e.g. with real investor pitch)
• internship in a company => work-integrated learning (WIL)

• are able to relate the foundational principles and concepts of requirements engineering (RE) to each other
• can explain its role in the software development lifecycle and industrial software production
• know RE frameworks and modeling techniques (e.g., UML, BPMN), and their applications in real-world scenarios
• know relevant RE processes and interfaces to other processes
• know concepts and recent research on product line and variability management

• apply best practices in addressing conflicting stakeholder requirements, ambiguous needs, and dynamic project goals
• model requirements with RE tools
• set up and integrate modern RE tools into tool chains and design flows
• derive requirements in a structured and comprehensive way

• effectively communicate with diverse stakeholders, including clients, developers, and end-users, to elicit and refine requirements
• work collaboratively in teams to deliver concepts and solutions, balancing multiple perspectives and interests
• facilitate workshops and collaborative activities to drive stakeholder alignment and consensus on requirements

• set up and lead RE in a cross-domain team
• develop a reflective understanding of their role as requirements engineers in contributing to successful systems
• recognize the ethical and professional responsibilities associated with translating stakeholder needs into solutions
• critically evaluate practices in RE to identify improvements and innovations in their work

• Definition, relevance, and challenges
• Role depending on system types and project characteristics

• Stakeholder identification
• Interviews, focus groups, and ethnography
• Brainstorming and collaborative workshops
• Creativity and innovation

• Requirements Specification (SRS) standards
• Informal methods: prototypes, storyboards
• Modeling requirements: UML, BPMN, user stories
• Tools: JIRA, Confluence, ReqIF

• Quality attributes: completeness, consistency, correctness
• Prototyping and user feedback
• Requirements testing strategies

• Prioritization techniques: MoSCoW, Kano, Weighted Scoring
• Traceability matrices
• Impact analysis for changes
• Versioning and change management

• Software product lines, adaptive systems and crowd-based systems
• Domain-specific languages
• Generative AI and natural language processing in RE

• Theoretical knowledge: lectures on requirements engineering
• Practical Skills: requirements engineering cycle, group work to train concepts and methods, to develop skills and to work on case studies
• Scientific Competences: research paper on literature review about RE topic

• Working Conference on Requirements Engineering: Foundation for Software Quality (REFSQ)
• IEEE International Requirements Engineering Conference (RE)
• Requirements Engineering Journal, Springer
• International Workshop on Requirements Engineering and Testing, at ICSE International Conference on Software Engineering, IEEE Press
• IEEE Transactions on Software Engineering
• IEEE Systems Journal
• Groen, E.C., Seyff, N., Ali, R., Dalpiaz, F., Doerr, J., Guzman, E., Hosseini, M., Marco, J., Oriol, M., Perini, A., Stade, M. (2017). The Crowd in Requirements Engineering: The Landscape and Challenges. IEEE Softw. 34, 44–52. https://doi.org/10.1109/MS.2017.33.
• Jarbele C. S. Coutinho, Wilkerson L. Andrade, and Patrícia D. L. Machado. 2019. Requirements Engineering and Software Testing in Agile Methodologies: a Systematic Mapping. In Proceedings of the XXXIII Brazilian Symposium on Software Engineering (SBES 2019). Association for Computing Machinery, New York, NY, USA
• Danyllo Albuquerque, Everton Guimaraes, Mirko Perkusich, Alexandre Costa, Emanuel Dantas, Felipe Ramos, and Hyggo Almeida. (2020). Defining agile requirements change management: a mapping study. In Proceedings of the 35th Annual ACM Symposium on Applied Computing (SAC ’20). Association for Computing Machinery, New York, NY, USA

• know research methods and tools of the digital transformation (scientific) domain
• know state of the art in a certain scientific field
• know open research questions in this field
• know relevant literature
• know how to document new findings according to scientific standards

• apply research methods and tools of the scientific domain
• apply appropriate research methodology
• apply deductive methods, especially literature review
• implement a project and create project results
• describe state of the art, methodology and findings in a scientific report

• Students can write scientific papers (in English)
• Students can present and defend results (in colloquium or at a conference)

• Students can plan and conduct scientific research in their field
• Students can compare own findings with state of the art and do a critical discussion
• Students can create new findings

• Writing of a scientific report (individual or group homework)
• Presentations to communicate and discuss the findings
• Individual review and feedback on papers and presentations

• MOD3-03 – Research Project (Thesis) + Colloquium
• P – Master Thesis + Colloquium

• Knows state of the art in a certain scientific field
• Knows open research questions in this field
• Knows relevant literature
• Knows methodology and tools to execute project
• Knows how to document new findings according to scientific standards

• Can analyze problems and derive requirements
• Can define and plan an own research project
• Can apply appropriate research methodology
• Can implement a project and create project results
• Can describe state of the art, methodology and findings in a scientific report

• Can solve complex technical problems
• Can compare own findings with state of the art and do a critical discussion
• Can run an own scientific research project and create new findings
• Can deliver results on a quality level, e.g. for a company
• Masters uncertainty and unknown topics in new area
• Can present and defend results (in colloquium or at a conference)

• Project work, in a scientific project or within an internship in industry
• Writing of a scientific report
• Presentations to communicate and discuss the findings
• E-learning course on scientific work and scientific writing
• Individual review and feedback on results, papers and presentations

• Knows relevant home automation systems and standards
• Know smart building concepts (e.g. VDC, BIM)
• Knows relevant trends and projects in Smart City
• Is aware of critical limitations, esp. safety and security issues

• Can design concepts for smart home/smart building/smart city systems
• Can implement IoT, Cloud and SW components into such systems
• Can apply state of the art tools and systems (e.g. KNX)
• Can select IoT and cloud platforms according to smart home/building/city requirements
• Can apply and configure Smart City platforms (e.g. FIWARE)

• Can discuss smart home/building/city systems with experts
• Can lead cross domain design in this domain
• Can contribute to Smart City Alliances (e.g. Dortmund Smart City Alliance)

• Lectures introducing concepts, methods and tools
• Project simulation (agile, virtual SW development projects with Scrum) on the case study of setting up a Smart Home Automation or Smart City platform. Several sprints are conducted over 2 months’ time. Review meetings with teachers and 2 reviews in the plenary
• Group work on writing a scientific paper, peer review by students and teachers. Excellent papers can be encouraged to submit at a conference, e.g. IEEE E-TEMS
• Presentations to communicate results

• Develop sophisticated software systems tailored to specified requirements, leveraging widely recognized design frameworks such as UML (Unified Modeling Language), SoaML (Service-oriented Architecture Modeling Language), or SysML (Systems Modeling Language)
• Demonstrate an understanding of the intricacies involved in creating scalable and maintainable system architectures

• Evaluate and apply appropriate architectural patterns, such as Microservices or Moduliths, to develop robust software solutions
• Tailor the architectural approach to address the specific needs and constraints of a given use case or application domain

• Create and implement scalable deployment strategies for distributed software systems, ensuring high availability and fault tolerance
• Utilize cloud platforms and container orchestration tools, such as Kubernetes, AWS, or Microsoft Azure, to deploy and manage applications efficiently in diverse operating environments

• Create and implement scalable deployment strategies for distributed software systems, ensuring high availability and fault tolerance
• Utilize cloud platforms and container orchestration tools, such as Kubernetes, AWS, or Microsoft Azure, to deploy and manage applications efficiently in diverse operating environments

• Introduction Microservice Architecture
• Introduction use case for the software system to develop
• Agile Methodologies in Software Development
• Requirements engineering
• Designing of the software system
• Implementation of the software system
• Deployment of the software system
• Testing of the software system  

• Object oriented modeling and design
• Architecture Design (Patterns, Frameworks, Libraries)
• Software Testing
• Tools
• Version control systems (Git, SVN, Mercurial SCM)
• Code management
• Ticket systems and bug tracker
• (Continuous) integration and release management
• Documentation
• Processes
• Classical software development
• Agile software development (Scrum)
• Requirements Engineering
• Project management, project planning, quality management

• Interactive lectures: Traditional lecture format enhanced with real-time discussion and interactive elements. If applicable, industry professionals, deliver guest lectures with additional industry insights
• Groupwork: Collaborative projects where students design and implement a software system for a given use case
• Hands-on Workshops: Practical sessions where students apply tools, methods and techniques introduced in class
• Self-Directed Learning and Research: Students explore specific areas of interest related to Microservice Architecture or service-based software systems through independent study and research
• Peer Reviews and Critique: Students provide constructive feedback on each other’s work during project development and pitch presentations

• MOD1-01 Innovation Driven Software Engineering
• MOD1-02 Software Architectures
• MOD1-04 R&D Project Management
• MOD2-02 Software-intensive Solutions

• Knows recent trends in Digital Transformation
• Knows the relevant scientific literature
• Knows practical cases

• Can do a structured literature review on a given topic
• Can design own research on the topic
• Can present research results

• Can systematically explore a new scientific field
• Can organize research work in an unknown field
• Can synthesize and summarize findings in a meaningful way
• Shows curiosity in scientific research

• Lecturers and industry presentations
• Individual literature research
• Assignments, e.g. writing of a paper

• Scientific & Transversal Skills 2 (MOD2-04)
• Research Seminar
• Research Project (Thesis) (MOD3-03)
• Master Thesis and Colloquium

Publications IDiAL, FH Dortmund:
https://www.fh-dortmund.de/en/idial/forschung/veroeffentlichungen_statisch.php

• Models for communication systems and other reference models
• Theoretical approaches to capacity planning and dimensioning based on statistical models and Markov chains
• Network algorithms for switching - Spanning Tree Protocol - and Routing - Open Shortest Path First
• Wide Area Network solutions, e.g. Multi Protocol Label Switching
• Virtualised Network Functions using CumulusVX and OPNSense as examples
• Network Management based on SNMP und deployment of Zabbix as network monitoring system
• Reference Architectures for company and data centre networks
• Networking in Cloud Computing

• Larry L. Peterson Bruce S. Davie: Computer Networks: a system approach, 2.ed., Morgan
  Kaufmann
• Douglas Comer / David L. Stevens: Internetworking with TCP/IP, Vol.1 und 2, Prentice Hall

• • terminology of machine learning systems
• • Development of machine learning systems in KNime or other languages like python
• • design, implementation and evaluation of machine learning systems
• • linear models
• • supervised and unsupervised learning
• • neural networks
• • clustering, k-means
• • nearest-neighbour algorithms and lazy learning
• • decision trees
• • combination models, random forest, AdaBoost
• • Deep Learning (convolutional neural networks (CNN), long short-term memory (LSTM), Transformer (BERT))
• • Deep Learning Concepts - Transfer Learning, Data Augmentation, Generative Adversarial Networks (GAN)
• • Explainability of models
• • Applications for different modalities (text, image, sound), Word2Vec
• • theoretical concepts of machine learning (bias-variance dilemma, No Free Lunch Theorem)
• • methods to improve generalization abilities (regularisation, feature selection, dimension reduction,
• complexity adjustment)
• • solution of real world tasks in form of miniprojects in collaboration with local companies
• Workshop with industrial partners presenting the results of miniprojects

• video lecture accompanying project work with final presentation,
• Flip teaching (inverted classroom) is used.
• completion of programming tasks on the computer, individually or in teams,
• lab practice with KNime

• Witten, E. Frank, M. Hall und C. J. Pal, Data Mining: Practical Machine Learning Tools and Techniques, 4. Edition, Morgan Kaufmann (2017) – electronic version via intranet access possible
• C. M. Bishop, Pattern Recognition and Machine Learning, Springer (2006)
• E. Alpaydin, Introduction to Machine Learning (Adaptive Computation and Machine Learning), Third Edition, MIT Press (2014)
• I. Goodfellow, Y. Bengio und A. Courville: Deep Learning, MIT Press (2016) – free version available https://www.deeplearningbook.org

• Graduates of the module master basic and advanced concepts of artificial intelligence and are able to apply current developments and methods of artificial intelligence to concrete practical issues in business informatics.
• The participants are able to confidently assess the benefits and limitations of the content and methods considered in relation to concrete practical applications of business informatics.
• The participants are confident in using current program libraries and are able to apply them to concrete problems in a project-oriented manner.

• The participants are able to independently deal with current developments in the field of artificial intelligence and its specializations and current applications in the field of business informatics and to comprehend the core statements.

• The participants are able to lead discussions on scientific issues (especially with regard to the applicability of the taught content for their field of study).
• The participants grasp the relevance of the taught contents for their field of study and are able to communicate this relevance adequately.
• The participants are able to discuss the challenges of the project tasks in project-oriented group work, identify possible alternative approaches and define, implement and evaluate justified approaches.

• Project work (50% of the final grade)
• Oral examination (50% of the final grade)

• Knows relevant home automation systems and standards
• Know smart building concepts (e.g. BIM)
• Knows relevant trends and projects in Smart City
• Is aware of critical limitations, esp. safety and security issues

• Can design concepts for smart home/smart building/smart city systems
• Can implement IoT, Cloud and SW components into such systems
• Can apply state of the art tools and systems (e.g. KNX)
• Can select IoT and cloud platforms according to smart home/building/city requirements

• Can discuss smart home/building/city systems with experts
• Can lead cross domain design in this domain
• Can contribute within the Dortmund Smart City Alliance

• Theoretical knowledge: e-learning modules on Smart Systems, tool tutorials
• Practical Skills: Projects, Labs & Exercises, small project with Smart Systems
• Scientific Competences: own research on Smart Systems

• Knows recent trends in Digital Transformation
• Knows the relevant scientific literature
• Knows practical cases

• Can do a structured literature review on a given topic
• Can design own research on the topic
• Can present research results

• Can systematically explore a new scientific field
• Can organize research work in an unknown field
• Can synthesize and summarize findings in a meaningful way
• Shows curiosity in scientific research

• Lecturers and industry presentations
• Individual literature research
• Assignments, e.g. writing of a paper

• Scientific & Transversal Skills 2 (MOD2-04)
• Research Seminar
• Research Project (Thesis) (MOD3-03)
• Master Thesis and Colloquium

• ACM Special Interest Group on Software Engineering (SIGSOFT)
• ACM Special Interest Group on Computers and Society (SIGCAS)
• ACM Special Interest Group on Mobility of Systems, Users, Data and Computing (SIGMOBILE)
• ACM Special Interest Group on Computer Human Interaction (SIGCHI)
• International Project Management Association, IPMA
• IEEE Transactions on Software Engineering
• IEEE Systems Journal
• ACM SGICAS Conference on Computing and Sustainable Societies (COMPASS)
• ACM/IEEE Symposium on Edge Computing (SEC)
• IEEE Transactions on Human-Machine Systems

• Graduates of the module master basic and advanced concepts of artificial intelligence and are able to apply current developments and methods of artificial intelligence to concrete practical issues in business informatics.
• The participants are able to confidently assess the benefits and limitations of the content and methods considered in relation to concrete practical applications of business informatics.
• The participants are confident in using current program libraries and are able to apply them to concrete problems in a project-oriented manner.

• The participants are able to independently deal with current developments in the field of artificial intelligence and its specializations and current applications in the field of business informatics and to comprehend the core statements.

• The participants are able to lead discussions on scientific issues (especially with regard to the applicability of the taught content for their field of study).
• The participants grasp the relevance of the taught contents for their field of study and are able to communicate this relevance adequately.
• The participants are able to discuss the challenges of the project tasks in project-oriented group work, identify possible alternative approaches and define, implement and evaluate justified approaches.

• Knows state of the art in a certain scientific field
• Knows open research questions in this field
• Knows relevant literature
• Knows methodology and tools to execute project
• Knows how to document new findings according to scientific standards

• Can analyze problems and derive requirements
• Can define and plan an own research project
• Can apply appropriate research methodology
• Can implement a project and create project results
• Can describe state of the art, methodology and findings in a scientific report

• Can solve complex technical problems
• Can compare own findings with state of the art and do a critical discussion
• Can run an own scientific research project and create new findings
• Can deliver results on a quality level, e.g. for a company
• Masters uncertainty and unknown topics in new area
• Can present and defend results (in colloquium or at a conference)

• Project work, in a scientific project or within an internship in industry
• Writing of a scientific report
• Presentations to communicate and discuss the findings
• E-learning course on scientific work and scientific writing
• Individual review and feedback on results, papers and presentations

• Knows state of the art in a certain scientific field
• Knows open research questions in this field
• Knows relevant literature
• Knows methodology and tools to execute project
• Knows how to document new findings according to scientific standards

• Can define and plan an own research project
• Can apply appropriate research methodology
• Can create own research findings
• Can describe state of the art, methodology and findings in a scientific report

• Can compare own findings with state of the art and do a critical discussion
• Can run an own scientific research project and create new findings
• Masters uncertainty and unknown topics in new area
• Can present and defend results (in colloquium or at a conference)