Digital Technologies

Course content: Logic; sets; relations and functions; combinatorics; algebraic structures; number theory and modular arithmetic; basics of graph theory

Course content: Programming language Python; imperative control structures, functions, data types; modelling of problems; general learning and solution strategies in computer science; development tools

Course content: Basic concepts of project management; project process organisation, structure and roles; necessary framework conditions for project initiation (resources, budget, deadlines, etc.); project implementation, controlling and reporting during project execution and project completion; communication, moderation and presentation in the project; special methods and procedures in project execution, such as estimation procedures, Kanban, retrospectives, reviews; dealing with requirements and changes; SCRUM
 

Course content: Basics of climate change, environmental pollution, and dwindling non-renewable resources; Introduction to the circular economy, sustainability, and related concepts (biocapacity, etc.); Sustainability goals; Feedback loops and tipping points; Implications of closed systems with a finite supply of resources; Technology-focused and technology-critical approaches towards sustainability; Circular Societies

Course content: In terms of content, students work independently on current practical issues relating to digitalisation. The course content primarily includes learning and applying the knowledge from the first semester, e.g. programming in Python and project management. At the end of the semester, all results of the project should be presented in a suitable form for the specific semester and role.

Teaching content: Vectors and vector spaces; matrices; linear mappings; linear equations systems; determinants; Euclidean vector spaces

Course content: Introduction to Java programming environment; basics of Java programming language; introduction to object-oriented programming; inheritance and polymorphism; organisation of programs in packages; parameterisable classes and the collection framework; writing/reading files; reflection; programming concurrent and distributed systems(threads / RMI); programming graphical user interfaces with Swing; design patterns; visualisation of program sequences and program structures with UML 2.x

Course content: Introduction to IoT and robotics as an example of mechatronic systems; sensors and actuators for IoT and robots; understanding (sensor) signals; control engineering for mechatronic (robot) systems; modelling and simulation of mechatronic (robot) systems with Octave/Matlab/Scilab; experiments on IoT, AGV and UGV

Teaching content (depending on field of application):
Autonomous Systems: Autonomous Systems
Circular Economy and Environmental Engineering: Behavioral and Environmental Economics
Digital Transformation: Digital Innovation Management
Energy: Thermodynamics
Industry 4.0: Automation Technology 1
Mobility: Road Traffic Systems

Course content: Basic concepts; Unified Modelling Language; Object Constrain Language; Object-oriented analysis; Object-oriented design; Object-oriented programming

Course content: Descriptive statistics; characteristics and visualisation of one- and two-dimensional frequency distributions; time series; basic concepts of probability theory; one- and two-dimensional random variables; inferential statistics; point and interval estimation; hypothesis tests (t-test, chi²-test)

Course content: Specification techniques for analysis and design: structure-oriented, operational and descriptive techniques; automatic code generation from design; validation and verification of software systems; testing and model checking

Course content: Tasks, usage and architecture of database systems; relational data model and introduction to SQL; conceptual modelling(entity-relationship model); relational design theory (normal forms, etc.); data integrity; query languages and query processing; transactions and multi-user synchronisation; database security (authorisation); connection to programming languages; overview of non-relational data models (NoSQL, XML, etc.)

Teaching content (depending on field of application):
Autonomous Systems: Basics of Automation Technology
Circular Economy and Environmental Engineering: Waste Management and Recycling
Digital Transformation: Business Information Systems 1: Basics of Business Processes and Information Systems
Energy: Fundamentals of Electrical Engineering 1
Industry 4.0: Computer-Aided Design
Mobility: Short Range Mobility and Bicycle Traffic

Course content: In terms of content, students work independently in practice on current issues relating to digitalisation. The subject matter primarily includes learning and applying the knowledge from the 2nd semester, e.g. software development.
At the end of the semester, all results of the project should be presented in a suitable form for the specific semester and role.

Course content: Network flow optimisation: optimality criteria and basic algorithms for minimum spanning trees, shortest paths, maximum flows, minimum cost flows; linear optimisation: duality theory, optimality criteria, simplex methods

Course content: Knowledge, methods and procedures for usable systems' production in which information technology systems interact with users;
Introduction: human-task software, development of software ergonomics in the context of historical development of information technology, laws and standards;
Basics: Human information processing and action processes, input and output devices, interaction techniques, activity design;
Human-centred development process: process models, needs and requirements analysis, specification and prototyping, evaluation;
Applications: selected current application examples with exercises from areas such as web interfaces, industrial automation or autonomous systems

Teaching content (depending on field of application):
Autonomous Systems: Microcontroller; Cyber-Physical Systems
Circular Economy and Environmental Engineering: Industrial Environmental Protection and Wastewater Technology; Business Models for Circular Economy
Digital Transformation: Business Information Systems 2: Technologies and Applications; IT Management in the Context of Digital Transformation
Energy: Air Conditioning Technology; Control and Electrical Building Technology
Industry 4.0: Additive Manufacturing; Computer-Integrated Manufacturing
Mobility: Railsystems; Traffic Control

Course content: In terms of content, students work independently on current practical issues related to digitalisation. The subject matter primarily includes learning and applying the knowledge from the 2nd semester, e.g. software development. At the end of the semester, all results of the project should be presented in a suitable form for the specific semester and role.

Course content: Risk management in digitalisation projects focussing on risks in the areas of safety, security, privacy and other ethical aspects; assessments and process reference models, brief overview of legal framework conditions; discussion of social impacts using case studies.

Course content: Basic concepts; process of data science projects; exploration and becoming acquainted with data; association analysis; cluster algorithms(k-Means, EM, DBSCAN, single linkage); classification(nearest neighbour, decision trees, random forest, logistic regression, naive Bayes, SVM, (deep) neural networks); (linear) regression; time series analysis with ARIMA; evaluation methods for learned models; using methods mentioned with libraries for the Python programming language

Teaching content (depending on field of application):
Autonomous Systems: Robotics and Actuators; Digital Communication Technology
Circular Economy and Environmental Engineering: Environmental Systems; Applied Modeling and Simulation
Digital Transformation: Digital Business Models; Leadership
Energy: Battery Systems Technology and Fuel Cells; Control Engineering
Industry 4.0: Metrology and Sensors, Digital Production
Mobility: Digitalization in Traffic; Traffic Management

Course content: In terms of content, students work independently on current practical issues relating to digitalisation. The course content primarily includes learning and applying the knowledge from the 2nd semester, e.g. software development. At the end of the semester, all results of the project should be presented in a suitable form for the specific semester and role.

Course content: Independent work on and documentation of a complex, longer-term project in the field of digitalisation; preparation of a practical report as proof of the knowledge acquired and the project worked on

Students work independently on a scientifically based project related to digitalisation. In the documentation, the students present the key aspects of the area of digitalisation, discuss the solution approaches and describe the solution developed. In doing so, students independently deepen their existing theoretical knowledge.