Written Test

Topics include fundamentals (mathematical reasoning; sets; mappings and relations; natural numbers), real numbers, sequences and series, limits and growth of functions, differential and integral calculus, Taylor expansion.

The students know the basics of calculus, which are an important prerequisite in all areas of computer science. They have the ability for formally correct (mathematical) argumentation and representation. By working in small practice groups, the students have the ability to work on problems together and to critically evaluate other students' solutions. By dealing with strictly formal content and tools, argumentative accuracy is developed and stamina is strengthened.

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Written Test

Topics include algebra (groups, rings, fields, polynomial rings, coset, and Lagrange's theorem) and linear algebra (vector spaces, linear mappings and their matrix representations, rank of a matrix, base changes, orthonormal bases, systems of linear equations and their solution using the Gaussian algorithm, determinants, eigenvectors and eigenvalues, orthogonal and symmetric matrices

Students gain knowledge of algebraic structures and linear algebra and their applications in computer science. They are able to reason about abstract algebraic structures and correctly apply the methods and algorithms of linear algebra to solve systems of linear equations and describe geometric facts. After this module, students have confidence in formally correct mathematical reasoning and its presentation.

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Written Test

Elements of programming, case distinctions and branching, composite and mixed data, programming with accumulators, higher-order functions, interactive programs, recursive data structures and recursive functions, pattern matching, designing programs, draft recipes, reduction semantics, and program equivalence.

Students know design instructions for the systematic design of computer programs and can use them appropriately. They know the characteristics of the functional paradigm and can assess its strengths and limitations. They can structure problems, describe them abstractly and then develop programs in a disciplined process. They can present their results in a comprehensible manner and explain details of their solution path explain their solution in technical terminology.

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Written Test

Modeling of data, class concept, composition and union of class references, class hierarchies, object-oriented modeling and programming, methods and parameter passing, encapsulation of data, abstract classes, visibility and access rights, imperative methods, GUI programming, debugging

The students know methods and tools of object-oriented modeling and programming and can use them appropriately. They know the characteristics of stateful programming and understand the necessity of encapsulating the state of objects. Students can implement and test basic computer science algorithms and data structures using imperative and object-oriented programming methods. In addition, students can effectively locate and correct errors in programs. They are prepared to effectively apply their programming skills in subsequent larger projects.

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Written Test

The module covers the topics of introduction to software engineering, software project management, software process models, requirements management, programming at scale, API and library design, distributed and concurrent software systems, module concept, version control, software quality (especially test processes and software metrics as well as program analyses), design by Contract, design patterns, code reviews, SCRUM.

Competencies: Students can name the essential areas of software engineering and classify them in the context of a software development project; they can use established software development tools in a targeted manner; they are able to perform basic quality assurance such as automated tests; they can design and implement software systems using basic object-oriented and functional design patterns.

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Written Test

This course provides students with the basic knowledge that is required to design and understand digital circuits. First, the so-called logic- and register-transfer-design is introduced and the topics Boolean algebra, switching algebra, combinational circuits, conjunctive and disjunctive minimal forms, flip-flops (RS, JK, D, T, etc.), circuit analysis and synthesis, digital standard components, memory structures (RAM, ROM, EPROM, Flash) and programmable logic (PLA, FPGA) are deepened. Subsequently, the physical fundamentals of the functioning and application of passive components (resistors, capacitors, coils) as well as semiconductor components (diodes, transistors) are discussed and the realizations in various semiconductor technologies are dealt with.

Students possess basic competencies in computer engineering. They know formal and programming language circuit description as well as the structure and function of all important basic circuits and arithmetic units. The students acquire the competence to design, analyze and optimize digital circuits independently. They will be able to use tools for hardware design as well as for the evaluation of characteristic properties such as power consumption.

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Written Test

Topics include multidimensional analysis, Fourier series, optimization (extreme value problems under constraints, Lagrange multipliers, algorithms in discrete and continuous optimization), topics from discrete mathematics such as number theory with applications in cryptology.

Students gain knowledge in multidimensional analysis, number theory and their application in cryptology and optimization. After this module, they are able to establish relationships between different mathematical subfields and to name their significance for computer science.

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Written Test

Topics include probability spaces, random variables, distributions, Independence, Law of Large Numbers, Central Limit Theorem, Stochastic Processes, Stochastic Models, Sampling, and Estimating & Testing.

Students receive basic knowledge in probability theory and statistics. They are able to describe and analyze simple random phenomena mathematically. They are able to apply basic stochastic methods in computer science (e.g. bioinformatics, randomized algorithms).

Georgii, H.-O.: Stochastik, de Gruyter; Krengel, U.: Einführung in die Wahrscheinlichkeitstheorie und Statistik, Vieweg;

Wolff, M., Hauck, P. und Küchlin, W.: Mathematik für Informatik und Bioinformatik, Springer

Written Test

Topics include interpolation and approximation, numerical integration, numerical differentiation, systems of linear equations, compensatory calculus, and numerical treatment of nonlinear equations. Note: If a separate course is not offered to computer science students, participation in the first two-thirds of the course Numerics offered in the Department of Mathematics is considered equivalent. In this case the exam will only refer to this part.

Students gain knowledge of basic numerical methods. They are able to analyze algorithms of numerical mathematics, in particular with respect to error propagation and stability, and to implement them.

Literatur wird in den jeweiligen Veranstaltungen bekannt gegeben.

Written Test

The module covers the topics introduction to software engineering, programming on a large scale, project organization, module concept, design by contract, tender specification vs. performance specification , design patterns (observer, model-view- controller, adapter, proxy), events and messages, code reviews, unit tests and project documentation. The specified competencies are acquired in specialized courses. Thus, the achieved grade is included in the final bachelor grade.

Students know methods and techniques for the design and programming of complex software in a team and are able to use them appropriately and professionally in practice. They can present their own contributions to the overall project clearly and competently and react flexibly to necessary changes. In addition, they can organize their project independently and determine the progress of the project. Students have also acquired the following competencies: presenting, organizing, communicating, problem-solving skills, and critical questioning.

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Written Test

The basic lecture provides an overview of the following five areas: Internet, Coding, Assembly Programming, Computer Architecture, Operating Systems and Power Supply. In all 5 areas, a basic system view is provided. The following topics are covered in the 5 areas:
Internet: Protocol layers and basic structure of the Internet
Coding: number representations and character encoding, source encoding, channel encoding, line encoding;
Assembler programming: basics, calling subroutines in assembler, using the stack, program translation and execution, (impact of) compiler optimization;
Computer architecture: Instruction Set Architecture, Application Binary Interface ,Structure of computers, Moore's Law, basic performance considerations; Von Neumann architecture, CISC/RISC architectures
Operating systems: Processor structure, pipelining, hazards, exceptions; memory technologiesand hierarchy, locality principles, caches, processes and process management, structure and operation of virtual memory, Translation-Lookaside Buffer (TLB), cache coherence with multiple processors,user/kernel mode; structure of storage media, failover, RAIDs; Virtual Machines, advantages of virtualization, virtualization methods, Virtual LAN (VLAN); I/O devices, handshaking protocols for buses, parallel and serial buses, PCI, USB, control of I/O devices by the processor,data exchange between I/O devices and main memory, Direct MemoryAccess (DMA), advanced topics in operating systems;Energy supply:Climate change, quantitative comparison of CO2 emissions,power grids, energy markets, energy transition, power/heat coupling, demand-side management.

The students know basics in the areas of Internet, coding, assembly language programming, computer architecture, operating systems and power supply. They will be able to explain important terms, interrelationships and advantages and disadvantages. They understand the basic structure and operation of the systems covered at various levels. They will be able to sketch and interpret their structures and modes of operation. They can recognize the theoretically acquired concepts in practice and apply what they have learned.

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Written Test

The basic lecture provides an overview of the following five areas: Internet, Coding, Assembly Programming, Computer Architecture, Operating Systems and Power Supply. In all 5 areas, a basic system view is provided. The following topics are covered in the 5 areas:
Internet: Protocol layers and basic structure of the Internet
Coding: number representations and character encoding, source encoding, channel encoding, line encoding;
Assembler programming: basics, calling subroutines in assembler, using the stack, program translation and execution, (impact of) compiler optimization;
Computer architecture: Instruction Set Architecture, Application Binary Interface ,Structure of computers, Moore's Law, basic performance considerations; Von Neumann architecture, CISC/RISC architectures
Operating systems: Processor structure, pipelining, hazards, exceptions; memory technologiesand hierarchy, locality principles, caches, processes and process management, structure and operation of virtual memory, Translation-Lookaside Buffer (TLB), cache coherence with multiple processors,user/kernel mode; structure of storage media, failover, RAIDs; Virtual Machines, advantages of virtualization, virtualization methods, Virtual LAN (VLAN); I/O devices, handshaking protocols for buses, parallel and serial buses, PCI, USB, control of I/O devices by the processor,data exchange between I/O devices and main memory, Direct MemoryAccess (DMA), advanced topics in operating systems;Energy supply:Climate change, quantitative comparison of CO2 emissions,power grids, energy markets, energy transition, power/heat coupling, demand-side management. 6LP IDS

The students know the basics in the areas of the Internet, coding, assembly language programming, computer architecture, operating systems and energy supply. They can explain important terms, connections and advantages and disadvantages. They understand the basic structure and functioning of the systems dealt with at various levels. They are able to sketch and interpret their structures and modes of operation. They can recognise the theoretically acquired concepts in practice and apply what they have learned.

6 LP IDS

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Written Test

Introduction: computational models, efficiency measures;
sorting methods: Quicksort, Heapsort, Mergesort;
Elementary data structures: lists, trees, graphs, dynamic search structures, hashing;
Graph algorithms: Patterning, shortest paths, spanning trees;
Algorithms on strings: pattern search;
Programming: learned algorithms and data structures.

Students have basic knowledge of fundamental data structures in computer science and of algorithms for fundamental problems. Within this framework, they are familiar with the independent creative development of algorithms and data structures. The students know the interactions between data structures and algorithms and can apply these to concrete examples. Based on the analysis techniques they have learned, they can evaluate simple algorithmic approaches according to their quality, efficiency and complexity. In addition, students are able to implement the algorithms and data structures they have learned.

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Written Exam

Topics include formal languages, and automata, computability, decidability and recursive enumerability, existence of undecideable problems, Rice's first theorem, complexity theory, time and space requirements, and NP-completeness.

Students have the ability to perform the standard constructions from the field of finite automata and regular expressions. They have an understanding of the phenomenon of non-computability and the frequency of its occurrence, as well as a basic understanding of the notion of NP-completeness and its motivation.

Kenntnisse der Vorlesungen "Mathematik für Infomatik 1: Analysis" (INFM1010) und "Theoretische Informatik 1: Algorithmen und Datenstrukturen" (INFM2420) werden empfohlen.

Exam + exercise grade

Database usage; database models and languages (types, declarativity, data independence, persistence); relational data model and SQL; normal forms, functional dependencies; entity-relationship model; relational algebra; recursive algebra; Recursive queries; Practical use (PostgreSQL)

This module provides a broad base of database system fundamentals (primarily: relational database systems). Students will be able to query, modify database systems. Students learn the basics of relational data models and their implementation in the form of SQL-based database systems. Students will be able to design and evaluate database schemas and query, modify database instances. Existing database systems can be assessed with regard to their quality and efficiency.

Kemper/Eickler: Datenbanksysteme: Eine Einführung
Heuer/Saake: Datenbanksysteme – Konzepte und Sprachen
Relationale Datenbanksysteme (Software und Manuals), u.a. PostgreSQL

Exam + exercise grade

This lecture deepens specific theoretical knowledge, implementation aspects and practical use of database technology. The focus is on topics that cannot be covered in detail in the general introductory lecture Database System 1. Objects of study are real (source-open) database systems as well as prototype replicas of selected components of database systems.

Students understand selected detailed aspects of database technologies. This ranges from the interfacing of external database applications to internals of the database kernel that ensure efficient database operation in the first place. Unlocking these complex details encourages and requires discipline as well as self-study of the materials provided. Students understand the runtime characteristics of database systems and are familiar with relevant benchmarks.

Klassische und aktuelle Forschungsartikel zum Thema

Written Test

Introduction and motivation of basic concepts and techniques in computer graphics. Elementary data structures and algorithms are presented from many fields.
Topics are: Ray tracing, light transport, signal processing, textures, image filters, color representation and perception, OpenGL programming, 3D splines and surface and visualization techniques.

Students know the most important algorithms and data structures for representing three-dimensional scenes (geometry, light sources, optical material properties, textures) as well as operations and methods for generating realistic images from 3D scene descriptions (rendering equation and OpenGL). You can implement simple rendering and interaction techniques.

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Written Test

Covered topics include: Fourier series, Fourier transform, properties of the Fourier transform, discrete Fourier transform, sampling and aliasing, linear operations, PSF, LSI systems, FIR and IIR filters, image reconstruction (Wiener filter), multiscale representation, wavelets, edge detection, segmentation, image mapping, cross-correlation, morphological operations.

The students know the mathematical basics of image processing and know which algorithms exist for the basic tasks in image processing and how they are applied. In the exercises, the students have learned to apply their theoretical knowledge to solve concrete problems in image processing and to implement appropriate implement the corresponding algorithms.

Es soll entweder (INFM1110 oder INFM1120) und (INFM1010 oder INFM1020) bestanden worden sein.

Written Exam

To be announced

To be announced

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Oral examination (written exam if there are a large number of participants)

The advances in modern high-performance computing and sensor technologies lead to increasingly large and complex data in many domains like the (life) sciences, medicine, physics, or engineering. Interactive visualization is often a crucial step to analyze these data. Scientific visualization is concerned with the depiction of data that has a spatial structure (mostly three-dimensional), for example medical volumes from CT or MRI scanners, or molecular structures. In this lecture, the steps of the visualization pipeline will be discussed, leading from the input data to the final image or the interactive rendering of the data set. This includes interpolation and filtering, mapping techniques, as well as the basics of (color) perception, computer graphics/rendering, and interaction. Visualization methods for different types of scientific data will be introduced, including particles, 3D scalar fields (volumes), vector fields, and tensor fields. In particular, the application of these methods for the visualization of biological as well as medical data will be discussed. This is, methods from Information Visualization (i.e., the visualization of abstract, non-spatial data) are not part of this lecture, as these are covered in BIO4364 - Visualization of Biological Data.

Students will
• know the most important concepts of scientific visualization (i.e., the graphical depiction of different types of spatial data, sampling, interpolation)
• know about visualization techniques for scientific data (e.g., particles, 3d scalar/vector/tensor fields)
• are able to implement these techniques on their own
• know how to apply scientific visualization effectively for the analysis of biological and medical data

Lecture slides will be made available for download.
C. Hansen, C. R. Johnson, “The Visualization Handbook,” Academic Press, 2005.
H. Schumann, W. Müller, “Visualisierung: Grundlagen und allgemeine Methoden,” Springer, 2000.
A. C. Telea, “Data Visualization: Principles and Practice,” A K Peters/CRC Press, 2nd edition, 2014.
M. O. Ward, G. Grinstein, D. Keim, “Interactive Data Visualization: Foundations, Techniques, and Applications,” CRC Press, 2nd edition, 2015.

Written Test

Internship with changing focus: Implementation of computer games or interactive 3D applications, use of special VR/AR hardware, programming of mobile graphics applications, implementation of visual special effects in animations

Students will be able to independently plan and execute a programming project in groups. Techniques for creating interactive applications and games and the use of suitable libraries are known and practiced.

Entwicklungsumgebung wird zur Verfügung gestellt

Written Test

Computer Games / Special Effects 2: Internship with changing focus: Implementation of computer games or interactive 3D applications, use of special VR/AR hardware, programming of mobile applications, implementation of visual special effects in animations

Computer Games / Special Effects 2: Students will be able to independently plan and execute a programming project in groups. Techniques for creating interactive applications and games and the use of suitable libraries are known and practiced.

Entwicklungsumgebung wird zur Verfügung gestellt

Written Test

This lecture covers the latest topics in the field of Visual Computing

The students are familiar with current methods in the field of visual computing and know how to apply them.

Vorlesungsfolien werden zum Download bereitgestellt.

To be announced.

Special topics in graphical computing, rendering algorithms, rendering hardware, computer vision and pattern recognition, modeling, learning techniques in CG and CV.

Students learned about special topics in the field of graphic data processing.

Hängen von den aktuellen Themen ab und werden zur Verfügung gestellt

Written Test

This module is designed to teach basic principles and simple algorithms from the field of statistical learning.
Topics include: different learning problems and approaches to solving them, basic principles of statistical learning (Bayes' theorem, decision theory, basic problems, evaluation of results), simple baseline models from supervised and unsupervised learning (density estimation, classification, clustering), ML in a social context.

The students know basic principles and methods of machine learning and are aware of their principal limitations. In the exercises, they have learned to solve small practical problems with the methods covered and to implement corresponding algorithms in practice.

It is strongly recommended that students have passed the modules INFM1110, INFM1120 und INFM2010 in advance.

Literature:
'Introduction to Machine Learning', 4th Edition, Ethem Alpaydin, MIT Press. Chapters 1-12 and 20.

'Pattern Recognition and Machine Learning' by Christopher Bishop, https://www.microsoft.com/en-us/research/people/cmbishop/prml-book

To be announced.

Implementation of programs with algorithms from the field of machine learning.

Students can independently (in small groups) plan and create programs to solve simple problems in the field of machine learning, applying their theoretical knowledge.

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To be announced.

Special topics in computer graphics, computer vision, and learning techniques in these areas, e.g. computational photography, rendering algorithms, rendering hardware and interactive systems.

Students have become familiar with special topics in the field of computer graphics/computer vision and are able to develop a topic based on given and self-researched literature, present and discuss it in front of the group and present the essentials in an understandable and correct way in a written elaboration.

Hängen von den aktuellen Themen ab und werden zur Verfügung gestellt

Written Test

In the lecture, after a short introduction to the biological basics, the most important algorithms of artificial neural networks and their theory are presented. In the exercise, the theoretical knowledge is deepened by solving practical tasks with neural network simulators.

The aim of this module is to provide basic knowledge about neural networks. Students learn about the most important network models and their properties. They learn to use them to solve pattern recognition problems (classification, regression). In some cases they also program network models themselves or use modern simulators (JavaNNS, JMatlab).

Skriptum zur Vorlesung, und Lehrbuch A. Zell: Simulation neuronaler Netze, Oldenbourg-Verlag

Internship performance including lecture and essay

Students become familiar with neural network simulators (JavaNNS, Weka, Matlab) and various network models and training methods in teams of about 3 students, and solve a real pattern recognition problem in teams of 2-3 students in the second half of the lab.

Students learn to apply the models from the lecture to a larger real-world problem. Students will also learn problem analysis, teamwork, time management, documentation, and presentation techniques.

Wird in der Vorbesprechung ausgeteilt.

Written Test

The module covers approximately the first half of the book by Stuart Russel, Peter Norvig: Artificial Intelligence, A Modern Approach, 3rd. Edition. This includes: Introduction, Foundations and History of AI, Intelligent Agents, Problem Solving by Search, Heuristic Search Methods, Local Search Methods, Searches with Nondeterministic Actions and Partial Observations, Search Methods with Adversaries (Adversarial Search), Search Methods for Games, Alpha Beta Pruning, Stochastic Games, Constraint satisfaction problems, Backtracking search, Logical agents, Agents based on propositional logic, Predicate logic and knowledge representation in it, Unification and lifting, Forward chaining, Backward chaining, Prolog, Classical planning, Hierarchical planning and multiagent planning, Knowledge representation. The concepts of the lecture are deepened in exercises and programming tasks with Lisp or Java . Students learn to solve problems with AI techniques independently. solve problems.

Students will have basic knowledge of artificial intelligence based on the most internationally known AI textbook by Russel/Norvig.

Skriptum zur Vorlesung, und Lehrbuch S. Russel, P. Norvig: Artifi- cial Intelligence: A Modern Approach, 3rd Edition, Pearson

Presentation and essay

Special topics in machine learning, changing annually depending on the topicality of the topics, e.g. artificial neural networks, support vector machines, kernel methods, Gaussian processes, graphical models, Markov processes, kernel applications in chemoinformatics and bioinformatics, evolutionary algorithms.

Students learned about specific topics in the field of machine learning.

Hängt von den aktuellen Themen ab und wird zur Verfügung gestellt

Written exam (in case of a small number of participants: oral tests)

Introduction to human perception and actuation, user interfaces, planning and execution of user tests, graphical and statistical evaluation of user tests, user-centered design, analysis methods, prototyping, heuristic evaluation, social aspects of technical systems.

Competencies: Students are familiar with the fundamentals of human information processing, various interaction interfaces for input and output, and the process and methods of user-centered software development. They can plan, execute and evaluate user tests. They have an overview of the importance of technical systems in society, in particular the use of assistance systems.

wird in der Vorlesung bekanntgegeben

Written Test

User-centered design, analysis methods, prototyping, usability heuristics, heuristic evaluation, aesthetic design principles, implementation and evaluation of user tests.

Students learn the basics of interaction design and are able to understand and apply design processes. This course focuses on a user-centered view of new technological systems. Students know methods for problem analysis and prototyping, basic aesthetic principles for designing user interfaces, and implementation possibilities with markup languages. They will be able to perform and evaluate heuristic evaluations and user tests.

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Written Test

Development and protocols for the web, Principle of dynamic web sites on the client and on the server, XML as well as XHTML, CSS, HTML5, CGI mechanism, PERL as CGI language, Dynamic web sites with PHP, Database connection with PHP, The Smarty template engine, Client-side web development with JavaScript, Document-Object-Model (DOM), Mixed web applications with AJAX, Electronic learning materials and communication forums in Moodle.

After this module, students will be able to independently develop simple web applications. They understand the common server- and client-side techniques for this. The students master various widely used programming languages for this purpose. Students will also be able to independently implement simple web applications with database connections.

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Written Test

Protocols and network technology for the web, the
Apache web server in detail, content management systems, esp. TYPO3, frameworks, especially ZEND framework, CakePHP and Ruby on Rails, software architectures for the web, classification of web applications, web services, media formats for the web (MIME), performance testing for web applications, project management for the WWW, techniques of the internet 2: Shibboleth and more, web security, legal aspects on the web: TKG, DSG, TMG and more

Students understand the principles of the Web and know how to evaluate different techniques. They understand how the web server works and can independently install, configure and operate web servers. They know different software architectures on the Web and can implement simple applications according to these. The student is actively familiar with the operation and application areas of various frameworks and content management systems. In addition, the student knows the current legal framework for the operation of a web server and is able to recognize and close the most important security gaps.

Walter, T.: Kompendium derWeb-Programmierung, Springer 2007 Kappel, G., Pröll, B., Reich, S., Retschitzegger: Web-Engineering, dpunkt 2004

Project work with written documentation

Basics of design, laws of design, typography, layout, design and baseline grid, image selection, image preparation for the web, effect and symbolism of colors, basics Adobe Photoshop and Indesign

Students will master the basic design of print and online media. They know basic typography and its areas of application and produce high-quality artwork in prepress. Likewise, they can prepare media for presentation on the web and other online media and independently design online media. The common tools are actively used by the participants.

J. Böhringer, P. Bühler, P. Schlaich:Kompendium der Mediengestaltung, Springer, 2008
T.Walter: Mediafotografie - von der analogen zur digitalen Fotografie, Springer 2005
P. Bühler: MediaFarbe – analog und digital: Farbe in der Medienproduktion, Springer, 2004
S. Radtke, P. Pisani, W. Wolters: Handbuch visuelle Mediengestaltung, Cornelsen, 2004
C. Runk: Grundkurs Typografie und Layout, Galileo Design, 2008

Written Exam

To be announced

To be announced

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Written or oral exam; Successful participation in the exercise is a prerequisite for the exam.

Programming languages are one of the most important intellectual inventions of the 20th century. The topic of this event is the basics of programming languages: What language concepts are there, what do they mean, how to use them. Some keywords about the topics covered: Lambda- Calculus, interpreters, evaluation strategies, continuations, fixed points and recursion, monads, objects and classes, type systems, module systems, macros, domain-specific languages, Scheme, Haskell, Scala, Java.

The students are able to evaluate and compare programming languages from a technical point of view. They can describe the meaning of above programming language constructs precisely using specialist terminology and implement them in the form of interpreters. They can estimate the meaning of the different programming language concepts for the programmer and apply them in a meaningful way.

wird in der Vorlesung bekanntgegeben.

Written or oral exam; Successful participation in the exercise is a prerequisite for the exam.

How does the translation of a high-level programming language into machine instructions work? An understanding of this is not only of interest to compiler developers, but any good programmer should know how modern compilers and virtual machines work: On the one hand, it allows a deeper understanding of what happens when a program is executed; on the other hand, many of the technologies from compiler construction can be usefully applied in many other programs. Some keywords about the content: parsing, abstract syntax trees, intermediate representations, data flow analysis, register allocation, optimizations, runtime systems and virtual machines, compilers for object-oriented and functional languages.

Students will be able to understand the different phases of a compiler. They can independently implement compilers for simple programming languages and understand the trade-offs and alternatives that exist when designing and selecting compiler technologies.

Andrew W. Appel, Modern Compiler Implementation in ML, Cambridge University Press.

Evaluation of the internship result

The goal of this practical course is the implementation of a part of a programming language. For this purpose, in the first half of the semester we work out various aspects of the implementation of a programming language (e.g. syntactic checking, type checking, intermediate stages (ANF, SSA, CPS), control flow) with the help of programming tasks. Afterwards, students choose a part of an existing or self-designed programming language in consultation with the organizer and implement this part in the second half of the semester.

Students will understand the structure and operation of compilers and related programs for implementing programming languages and be able to describe them using specialized terminology. They are able to implement a simple programming language correctly and professionally on their own, and to present and justify the chosen solution.

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Written Test

Applied concepts and techniques related to programming languages that go beyond introductory lectures and prepare students for writing a bachelor's thesis.

Competencies: Students possess in-depth knowledge of selected concepts of programming languages and corresponding implementation techniques. They can evaluate concepts and techniques with regard to their usability in a specific application context and use them professionally.

Wird in den jeweiligen Veranstaltungen angegeben

Exam + exercise grade

Applied concepts in practical computer science that go beyond introductory lectures and prepare students to write a bachelor's thesis.

Students possess in-depth knowledge of selected areas of practical computer science, can evaluate concepts in terms of their usability in a specific application context and apply them in a professional manner.

Wird in der Vorlesung bekanntgegeben.

Written or oral exam; Successful participation in the exercise is a prerequisite for the exam.

The goal of this course is to provide knowledge on how design and programming techniques can improve the effectiveness of developers throughout the software lifecycle. In addition to classic topics such as design and architecture patterns, design heuristics, and framework design, we will learn about a wide range of tools and programming techniques, for example for refactoring or implementing domain-specific languages. You will learn techniques from both research and industrial practice and deepen your knowledge by reading scientific articles and experimenting with practical tools.

Students are able to understand and apply design techniques such as design patterns. They can evaluate a software design and understand the trade-offs between modularity, extensibility, performance, etc. Students will be able to use technical terminology to describe the relationship between programming languages and design techniques and will be able to use advanced programming techniques in modern programming languages to design software.

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Exam + exercise grade

This course uses the Haskell programming language to explore fundamental and practical functional programming concepts. The first three weeks of the course introduce students to Haskell, after which more advanced ideas of the functional paradigm are addressed: algebraic data types; parametric polymorphism; type classes; domain-specific languages and their embeddings; monads; parallelism. The material will be taught by of slide sets, blackboard notes and live coding.

Students will be able to understand basic and advanced concepts of functional programming in Haskell. Students describe complex data structures using the Haskell type system and independently develop programs to solve challenging algorithmic problems. Advanced methods for the abstraction of both data (e.g. generalized algebraic data types) and behavior (e.g. Monad Transformer) can be analyzed and created. Students develop access to advanced literature and research topics in functional programming.

Bird: Thinking Functionally

Hutton: Programming in Haskell

Bird/Wadler: Introduction to Functional Programming

Approval of the internship project during the semester, presentation and elaboration

The goal of this internship is to learn the practical use of advanced programming techniques, for example from the field of functional programming or compiler technology. For this purpose a larger project is accomplished in the context of the practical course for learning the respective programming techniques.

Students are able to master the complexity of a medium-sized programming project. They are able to use advanced programming techniques in the subject area of the internship in a meaningful and targeted manner. Students will be able to adequately present the status of their project and work effectively in a team.

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Written Test

inhalt 3220

goals 3219

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Project, presentation and elaboration

Teams of about 3 students work on a current task in the area of CI in Games. They program or extend a computer game with intelligent, typically self-learning agents. In particular, the potential for autonomous development of self-learning artificial intelligences is explored and evaluated.

Students could integrate intelligent agents into computer games. In general, they gain hands-on experience integrating intelligent mechanisms into computer games and simulation environments. They develop an understanding of how fast artificial agents can learn. In particular, they understand the interplay between the complexity of the game environment, the power of the learning algorithm, and the focus (bias) of the learning algorithm to discover certain structures in the environment.

Spezifische Informationen zu den Aufgabenbereichen werden gestellt. / Grundwissen in Künstlicher Intelligenz, Kognitiven Architekturen und dem Maschinellen Lernen sind hilfreich aber nicht zwingend notwendig.

Exam

Introduction and motivation of basic statistical methods using practical examples from neuroscience, perception research and image processing. The focus lies on the practical application of statistical methods and their implementation in Python. The following topics are covered: Discrete and continuous probability distributions, descriptive statistics (e.g., measures of location, dispersion, and correlation), inductive statistics (e.g., regression, generalized linear model (GLM)), and exploratory statistics are covered. Furthermore, the lecture will cover the introduction and application of probability distributions. Finally, a short introduction into Python and the use of notebooks will given in order to facilitate the use of the required statistical packages.

Students learn basic statistical methods, apply them and implement them in software. They are able to plan and evaluate experiments themselves and to avoid typical errors in experimental design. Furthermore, they can critically evaluated results presented in the literature.

Fahrmeir, Künstler, Pigeot, Tutz: Statistik; Springer-Verlag. /
Stahel: Statistische Datenanalyse; Vieweg & Sohn. /
Zusatzliteratur wird in der Vorlesung bekannt gegeben.

project 60%, presentation and documentation 40%

Teams of about 3 students work on a current task in the field of virtual reality; typically in Unity. This usually involves functionality enhancements, content generation, data acquisition and the integration of sensors (e.g. Vicon, LeapMotion, eye tracking, intertial tracking, etc.).

Students gain hands-on experience working with and enhancing virtual reality environments and interacting with them online. They will be able to program and activate a virtual reality environment. They will also know how to immerse and interact effectively with such an environment using appropriate tracking methods. You will also be able to effectively record data from VR interactions online and synchronized accurately over time.

Spezifische Informationen zu den Aufgabenbereichen werden gestellt. / Erfahrungen mit Simulationsumgebungen, VRs, und insbesondere Unity etc. sind hilfreich aber nicht notwendig.

Written exam (in case of a small number of participants: oral tests)

IT service management comprises all methods and measures for IT management. The goals for IT originate from the supported business and support is provided in the form of IT services. A key qualitative aspect is the provision of IT services with a required level of security. The merging of IT with many other areas in companies and in everyday life creates new challenges and opportunities. In this lecture, the methods and measures for IT service management are covered and the necessary organizational knowledge is conveyed through application examples in the area of interfaces. Information security management is considered with the components IT security and data protection both methodically and practically. The contents are: Methods in IT Service Management, interfaces in the area of ITSM (methodical and practical), project management in IT, requirements management, portfolio management of an IT service provider, information security management, data protection and data security, areas of application of IT security, certifications, standards and laws

The students have basic knowledge of IT organization, its structure, processes and basic knowledge of IT projects and project management. Using established frameworks (ITIL) and standards (ISO 20000), students can understand and manage complex IT service structures. In doing so, they can describe, control and further develop the processes used.

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Written Test

In this module, an overview of the semiconductor technology used and layout design is provided, and calculation methods for circuit dimensioning are introduced. Emphasis is placed on circuit simulation techniques, practicing design, analysis and selection of basic circuits, estimating limitations and costs, and estimating possible future technology developments. The lecture is organized as follows: Introduction to the terminology of integrated circuits, circuit simulation, outline of semiconductor technology and packaging, basic circuits and sizing criteria, theory of the MOS transistor.

The students understand the concepts of circuit technology for integrated, digital CMOS circuits. This enables them to understand integrated circuits and to solve the problems that frequently occur in this context in industrial practice, such as circuit dimensioning, in a results-oriented manner. Through the accompanying exercises, students deepen the knowledge imparted in the lecture by applying it to concrete problems. The independent work in small groups promotes personal responsibility and teamwork of the students.

Rabaey, Chandrakasan, Nikolic: Digital Integrated Circuits, a design perspective; 2nd ed. Pearson Education, Prentice Hall, 2003. J. Lienig: Layoutsynthese elektronischer Schaltungen; Springer, 2006.

Written Test

The aim of the practical course is the computer-aided application of essential concepts for the circuit design of integrated circuits (chip design) taught in lecture and tutorial. In the course of the internship, students can learn how complex chips are developed using state-of-the-art design tools. In cooperation with the company Cadence, the participants gain insight into the MMSIM technology and learn the practical handling of the current custom design platform Virtuoso and the visualization tool Viva. The practical course is structured as follows: Modeling of components and basic circuits, Generation of netlists, Use of different types of circuit simulation analysis, Circuit simulation of SPICE descriptions with Cadence Virtuoso Spectre, Analysis and consideration of physical phenomena such as threshold voltage and substrate effect, Determination of subthreshold currents and static dissipation, Simulation-based circuit dimensioning.

goals 3312

Rabaey, Chandrakasan, Nikolic: Digital Integrated Circuits, a design perspective; 2nd ed. Pearson Education, Prentice Hall, 2003. J. Lienig: Layoutsynthese elektronischer Schaltungen; Springer, 2006.

Written Test

This module covers the fundamentals, system aspects, storage media and basic applications of multimedia technology. The Shannon sampling theorem and pulse code modulation (PCM) form the basis for processing digital audio and video data. From this, various techniques have been developed that are specialized for the respective medium. Audio technology includes music and speech processing, video technology is mainly based on the development of digital television up to current video streaming applications. The data rates of these media require appropriate compression methods, which can be realized in hardware as well as in software. In addition, modern storage media for recording and playback of multimedia data are presented and the creation of multimedia content as well as techniques for storage and search in multimedia databases are discussed.

The students are familiar with current techniques in the field of multimedia. Particularly against the background of the highest demands on the quality of multimedia data and increasing broadband networking, the students know the corresponding key techniques. The students understand the functionalities and possibilities of these technologies. They are thus able to apply them in practice in a problem-adequate manner. The exercises are worked on in small groups. This enhances the students' sense of responsibility, cooperation and communication skills.

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Written Test

Complementary to the module Fundamentals of Multimedia Technology, this accompanying practical course serves to deepen the contents taught. In groups of max. three participants, the topics are put into practice through appropriate tasks. At the beginning there is an introduction to different image formats, their creation, conversion and specific properties. This is followed by the specific processing of image data using suitable tools. Another focus is on audio and video formats, their properties and creation using selected formats as examples. Comprehensive basic knowledge about the corresponding techniques and procedures, e.g. DCT and wavelets, is imparted. The implementation of this basic knowledge in multimedia applications is carried out using the example of BD mastering, multimedia applications on mobile devices, video conferencing and the handling of multimedia databases and media servers with a focus on suitable methods of content analysis and description.

Students will be able to practically apply the concepts from the module "Fundamentals of Multimedia Technology". They can specifically process multimedia data, such as audio/video data, and create query algorithms. They can evaluate different algorithmic strategies and apply them appropriately to the situation. Students know the advantages and disadvantages of DCT and wavelet transforms and can apply them to concrete examples.

Das Modul INF3321 Grundlagen der Multimediatechnik kann parallel belegt werden.

Literatur:
• R. Malaka, A. Butz, H. Hußmann: Medieninformatik - Eine Einführung;
Pearson Studium, 2009.
• W. Burger, M.Burge: Digitale Bildverarbeitung: Eine algorithmische Einführung
mit Java, Springer Vieweg, 3. Auflage 2015.
• K. D. Tönnies: Grundlagen der Bildverarbeitung; Pearson Studium, 2005.

Exam, exercise performance can flow into the exam as bonus points

Protocols and standards, OSI model, switching principles: Bridges, Switches, Routers; IP Addressing, IPv4/IPv6, ARP/NDP, DHCP, ICMP, Intradomain and Interdomain Routing, Flow and Load Control, Transport Protocols, UDP, TCP, Sockets, Domain Name System (DNS), Application Protocols, Firewalls, Network Address Translation (NAT), Peer-to-Peer Networking.

Students have a basic understanding of the operating principle and organization of the Internet. They can correctly apply important terms of the subject area and have a sound basis for in-depth studies in the field of communication networks.

Kurose, Ross: “Computer Networking: A Top-Down Approach”
O. Bonaventure: “Computer Networking : Principles, Protocols and Practice”,
http://inl.info.ucl.ac.be/cnp3

Graded internship attempts consisting of theory and practice with a final exam or oral exam

Introductory lecture units for each experiment, practical exercises at home to get to know the experimental environment (Linux command line, basic commands for network administration, recording traffic) as well as graded presence exercises in the experimental lab on the following topics: Network security, attacks and attack defense, VPN, Wi-Fi, selected application protocols.

Students are able to work in a team and have perseverance in solving technical tasks. They are able to independently research further information on the Internet and to read, understand and implement English technical texts. They can independently carry out simple configurations of computer networks and experimentally evaluate properties of basic protocols.

Wird während des Praktikums zur Verfügung gestellt.

Exam and possibly exercise grade

Applied technical concepts in communication networks that go beyond introductory lectures and prepare for writing a bachelor's thesis.

Students possess in-depth knowledge in the field of communication networks and are able to evaluate concepts in terms of their usability in a specific application context and use them professionally.

Wird in der Vorlesung bekanntgegeben.

Written Test

The lecture "Compiler Construction" is offered in this module regularly in the winter semester:
In this lecture, application-oriented concepts and techniques of programming languages and compiler construction are taught.
Specifically, the phases of compiler construction are first introduced using a Java compiler. The functional programming language Haskell is used as implementation technique. For this purpose, the necessary basics of functional programming are taught, building on the knowledge of the basic lecture.
In the second part of the course, students will implement a mini-Java compiler in group work using the techniques they have learned.

to be added

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Written Test

This module deals with the basic structure of modern computer systems. Topics include methods for classifying and evaluating computer architectures, pipelining for accelerated instruction processing, memory hierarchy and caches, main memory technologies, virtual memory management, jump prediction techniques, communication between processor and peripherals, and basic principles of hardware and computer design.

Students have a basic understanding of the structure, organization and operating principle of computer systems. This enables them to evaluate, compare and select microprocessor systems for different areas of application. Furthermore, the acquired knowledge enables the students to understand the relationship between hardware concepts and their impact on software. This enables the course participants to develop system-related functions as well as efficient programs. Through the accompanying exercises, students deepen the knowledge imparted in the lecture by applying it to concrete problems. Since the exercises are to be worked on independently in small groups, the students' ability to work in a team is trained in addition to their personal responsibility.

• David A. Patterson & John L. Hennessy; Computer Organization and Design RISC-V Edition: The Hardware / Software Interface 2. Auflage; Morgan Kaufmann, Elsevier, 2020.

• D. A. Patterson, J. L. Hennessy: Rechnerorganisation und Rechnerentwurf: Die Hardware/Software-Schnittstelle; Oldenbourg Wissenschaftsverlag, 4. Auflage, 2011.

• J. L. Hennessy, D. A. Patterson: Computer Architecture: A Quantitive Approach; Morgan Kaufmann Publishers Inc., 6. Auflage, 2018.

Written Test

The practical course deepens the following topics of the module Fundamentals of Computer Architecture through practical tasks: performance evaluation of computer systems, instruction execution in processors, design and implementation of system-related functions, optimization of programs using the knowledge of instruction processing sequences, system and hardware design, virtual memory management as well as the development and application of simulators for system analysis.

The students are able to apply and deepen the knowledge learned in the module "Fundamentals of Computer Architecture". They are able to analyze and solve corresponding practical problems and process tasks in industrial practice in a results-oriented manner. The tasks are worked on by the students themselves in small groups. In addition to teamwork, communication and conflict skills, this also trains the students' sense of responsibility.

• D. A. Patterson, J. L. Hennessy: Computer Organization and Design: The Hardware/Software Interface; ARM Edition (basierend auf 5. Auflage) Morgan Kaufmann, Elsevier, 2017.
• J. L. Hennessy, D. A. Patterson: Computer Architecture: A Quantitive Approach; Morgan Kaufmann Publishers Inc., 6. Auflage, 2018.

Written exam (in case of a small number of participants: oral tests)

The module Fundamentals of Robotics focuses in particular on stationary robots (manipulators). Introduction, goals and applications of robots, spatial coordinates and transformations, manipulator kinematics, inverse manipulator kinematics, velocities and static forces, manipulator dynamics.

The aim of this module is to provide basic knowledge about robotics. Students learn methods for describing the kinematics of robots and for solving position and path planning tasks. They learn about areas of application, drive forms and characteristics of industrial robots and can apply this to real problems.

Skriptum Robotik 1 (Zell) nach Lehrbuch, weitere Lit. wird zu Beginn der Vorlesung bekanntgegeben

Exam or presentation and essay

This module deals with current topics in the field of robotics. These are taught to students using current literature from research and industry. The module is primarily aimed at students who wish to acquire advanced knowledge in this area.

Competencies :The students have an insight into current topics in robotics. Self-discipline as well as reading and learning skills of the students are trained by working on the topics independently. Moderation competence, rhetoric and critical ability of the students are particularly improved by the presentation of the topic in front of an expert audience.

Aktuelle Literatur, die in der Vorbesprechung bekanntgegeben wird.

Written Test

inhalt 3400

goals 3399

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Written Test

This module is about providing the basics for the field of algorithms. This module is thematically and methodologically connected to the compulsory module Algorithms. It covers a wide range, from the theoretical conception of problem solving methods, different complexity classes and application areas to practical aspects such as algorithm engineering. Topics include graphs and networks, randomized algorithms, linear programming, approximations, parametrization and Parallelism

Students demonstrate advanced knowledge of methods for data structures and algorithms, particularly for various classes of algorithms such as graph algorithms, randomized algorithms, parameterized algorithms, geometric algorithms, and parallel algorithms. For the individual topics, students can independently apply the methods to case studies and solve them, including in particular the application of proofs of correctness and efficiency analyses. The students can develop simple algorithm ideas themselves and design the corresponding analyses and practical implementations.

Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms; Mehlhorn, Näher: LEDA - A platform for combinatorial and geometric computation;
Papadimitriou, Steiglitz: Combinatorial optimization : algorithms and complexity

Written Test

This course covers basic graph and network algorithms with emphasis on applications. Important methods are presented for various applications, including network analysis, clustering of data, visualization of graphs, etc., and their implementation to the requirements of the corresponding application is discussed. This will be accompanied by a practical course. Topics include network analysis, pattern search, clustering, and graph drawing.

In this module, students gain advanced knowledge in graph and network algorithms. They can formalize simple and also more difficult problems from different application areas and apply graph and network methods within the formal basics. (Simple) extensions of the basic methods can be designed and realized by the students independently.

Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms Mehlhorn, Näher: LEDA - A platform for combinatorial and geometric computation Papadimitriou, Steiglitz: Combinatorial optimization : algorithms and complexity

Written Test

inhalt 3414

goals 3413

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Written exam (in case of a small number of participants: oral tests)

Topics include complexity measures and their basic relationships, hierarchy theorems, reduction and completeness, alternation and circuits, the polynomial hierarchy, and complexity of approximability issues.

The students have an overview of the structure of the most important complexity classes and therefore a frame of reference for the complexity classification of combinatorial problems. They have developed an awareness of the seemingly notorious difficulty of combinatorial problems and the formal uncertainty of this situation.

Hopcroft u. Ullman, Introduction to automata theory, languages and computation, 1979 Rogers, The theory of recursive functions and effective computability, 1989 Arora and Barak. Computational complexity: a modern approach, 2009.

Written Test

inhalt 3441

goals 3441

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Written exam (in case of a small number of participants: oral tests)

Topics include lossless data compression, prefix codes and entropy, dictionary techniques, B-W transform, run-length encoding, fax, lossy case, quantization, differential encoding, subband encoding, transform encoding.

Students will have a basic understanding of the capabilities and limitations of data compression, an overview of the major techniques and knowledge of how they work, and the ability to use standard techniques.

Strutz: Datenkompression

Written Test

inhalt 3460

goals 3459

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Written Test

Fundamentals of propositional logic and first-level predicate logic. This includes, in particular, logical deduction systems and semantics of predicate logic languages as well as, as a central theorem, the completeness theorem and its applications.

Students will be able to work independently with term structures and apply logic as a language for modeling and specifying problems. The design, implementation and application of logic concepts of various kinds will be practiced. Students will also become familiar with the limits of expression of formal concepts. At the same time, this strengthens the ability to deal fundamentally and critically with the scope and application possibilities of formal tools.

D. van Dalen, Logic and Structure, Springer-Verlag, 2008. P. Schroeder-Heister, Skriptum Mathematische Logik (siehe Homepage des Veranstalters)

Graded assignments

Implementation of mechanical proof methods from lecture INF3482 Automatic Proof -- Fundamentals in approximately 5 exercises.

Students gain basic knowledge in the implementation of automatic proof methods and their capabilities and possible applications. They will be able to evaluate the practical relevance of mathematical logic for computer science using concrete examples.

Aufgabenbeschreibungen, Dokumentation der verwendeten Systeme

Written Test

Elementary basics of logic are presented. This includes the syntax and semantics of propositional and first-order logic, normal forms, and logical calculi such as the resolution calculus and the calculus of natural deduction.

Acquisition of basic logical skills that are essential for computer science.

Literatur: siehe Homepage des jeweiligen Veranstalters.

Hinweis: Diese Veranstaltung entspricht der früheren Veranstaltung INF2620 (Pflicht für Studierende des B.Sc. Informatik nach PO 2015 Pflicht; zu belegen im Modul "Logik & Proseminar (übK)" [INFM2620]).

Written Test

inhalt 3489a

goals 3489a

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Written Test

inhalt 3489b

goals 3489b

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Written Test

The contents are alternating. Each module covers a fundamental chapter of theoretical computer science. After an introduction to this area, important topics are covered.

goals 3499

In diesem Modul erhalten die Studierenden eine Einführung in ein Gebiet der theoretischen Informatik. Nach Abschluss des Moduls haben sie einen Überblick und grundlegende Kenntnisse in diesem Gebiet und sind in der Lage, eine Bachelorarbeit in diesem Gebiet zu schreiben.

Acceptance of the programming project during the semester

This practical course complements the corresponding module, which consists of lecture and exercise. Here, selected methods from the lecture are implemented in application scenarios, tested and documented.

The students can implement several of the methods in a small project. This implementation ranges from requirements analysis, design and implementation to text and documentation.

Originalliteratur wird bekanntgegeben

Weekly team meetings and final evaluation

Research, computer-aided teaching methods, supervision and implementation of exercises and classroom exercises accompanying the lecture Introduction to Computer Engineering, computer-aided organization of exercise operation by means of CIS, recognition and assessment of knowledge gaps, evaluation of the complexity of exercise tasks, independent development of tasks and sample solutions, correction and evaluation with and without computer support, search for plagiarism.

Students have a good knowledge of the material covered in the lecture "Introduction to Computer Engineering", know how to position it in the context of computer science and can talk about it independently as well as work out their own examples and tasks and guide other students in solving the exercises. They know the basics of group communication and motivation, gain experience in guiding independent work and can thus provide assistance with learning problems.

W. Schiffmann, R. Schmitz. Technische Informatik 1: Grundlagen der digitalen Elektronik. 5. Auflage, Springer, 2004.

Presentation and essay

Alternating topics from application areas of discrete mathematics in computer science.

For the concrete course offers in a particular semester please refer to the course catalogue in alma.

The students work independently on a limited topic from the field of discrete mathematics. They are able to present this topic in a structured and comprehensible way, to respond to contributions to the discussion and to summarise it in a written paper. The participants are able to give their fellow students appreciative feedback in the context of their presentation.

wird in der 1. Sitzung bekannt gegeben / will be announced in the first session.

Presentation and essay

Several topics from one subfield of theoretical computer science are covered per course.

The students are able to independently familiarise themselves with a topic from an area of theoretical computer science using written sources and to present this to others in a presentation. In doing so, the understanding must be sufficiently advanced to be able to answer questions and further questions from the students and supervisors.

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Presentation and essay

The proseminar includes the elaboration of written sources under supervision on topics from the field of Efficient Algorithms. The presentation and the written summary conclude the seminar work. Active participation in the individual sessions is an important part of the proseminar.

The students can independently work out a limited subject from the field of Efficient Algorithms from a written source, understand it and present it in the form of a prensentation and also represent it in a discussion in front of a plenum. In addition to the oral presentation, they can present and summarise the elaborated topic in writing.

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Presentation and essay

Different topics from the field of graph theory are covered per course. Examples: Planarity, network flows, colorability, context.

From summer term 2024 on, this proseminar will be offered as proseminar "Beweise aus dem Buch" in the module "Applications of Discrete Mathematics".

The students have a basic overview of graph theory and its application as well as in-depth knowledge of a topic in graph theory. The students are able to independently familiarise themselves with a topic from one area of graph theory using written sources and to present this to others in a presentation. In doing so, the understanding must be sufficiently advanced to be able to answer questions and further questions from the students and supervisors.

wird in der 1. Sitzung / zu Beginn der Vorlesungszeit bekannt gegeben

To be announced.

The proseminar includes the elaboration of written sources on topics from the fields of computer graphics and image processing under supervision. Presentation and the written summary conclude the seminar work. Active participation in the individual sessions is an important component of the proseminar.

Students can present and critically discuss simple procedures from the fields of computer graphics and image processing.

Hängt von den aktuellen Themen ab und wird zur Verfügung gestellt

Presentation and essay

Machine learning methods play an important role in data analysis and modeling in both industry and research. These methods can learn models from data and apply them to unknown instances. Examples of practical applications include character recognition, image recognition, shopping cart analysis, spam filtering or property prediction of chemical compounds. Basic machine learning techniques, their theoretical foundations and their practical applications are presented. In addition, validation strategies and parameter optimization methods are presented.

In addition to the subject-specific skills of the proseminar, students also learn how to scientifically analyse a topic, prepare a scientific presentation, give a presentation, communicate with an audience, engage in critical scientific discourse and write a scientific paper on their seminar topic.

Literatur wird in der Vorbesprechung angegeben.

Presentation and essay

Machine learning plays an important role in bioinformatics and chemoinformatics for data analysis and modeling. Basic machine learning methods, their theoretical foundations, and their practical applications in bioinformatics (e.g., in sequence analysis, protein similarity analysis, drug design, protein-ligand interactions, transcription factor binding site prediction, etc.) are presented. In addition, validation strategies and parameter optimization methods are presented.

Machine learning in bioinformatics: In addition to the subject-specific skills of the proseminar, students also learn how to scientifically analyse a topic, prepare a scientific presentation, give a presentation, communicate with an audience, engage in critical scientific discourse and write a scientific paper on their seminar topic.

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Presentation and essay

Elementary topics from mathematical logic, which can only be touched upon in the module "Lecture Mathematical Logic'', will be deepened by presentations of the students.

In addition to the competence in the content of mathematical logic (see module description "Mathematical Logic'' ("Mathematische Logik")), students learn to work out an elementary topic of mathematical logic independently, to communicate it to others through a presentation and to set it down in writing in a formally precise manner.

Literatur und Lernmaterialien werden jeweils im Netz bereitgestellt

Written Test

inhalt 3660

goals 3660

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Written Test

inhalt 3661

goals 3661

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Presentation and essay

Changing topics from the field of communication networks.

Students can understand and process a topic from written sources, summarise it in a self-prepared paper and present it independently in the form of a presentation with discussion.

Wird in der Vorbesprechung bekanntgegeben.

Presentation

The participants of this seminar each work on a selected topic of the annual ACM International Collegiate Programming Challenge (ICPC). This includes the conception of proposed solutions and their implementation. Participants communicate these solutions in the form of an approximately 30-minute presentation and demonstrate the resulting software. Equal emphasis is placed on (a) content-related aspects and (b) questions regarding presentation technique. In addition, a compact written elaboration summarizes the solution to the problem.

Students will be able to adequately select appropriate programming paradigms and languages for problem solving. Reading and learning skills are acquired. The compact and effective presentation of the acquired knowledge in the form of presentation and text is learned. The student acts confidently in front of the plenum. Self-discipline, critical faculties, language skills and empathy are promoted and challenged. As listeners, the participants are able to give their fellow students critical but fair feedback on the content and formal aspects of the presentation.

Ausgewählte Originalaufgaben des ACM ICPC Programmierwettbewerbes Literatur zu rogrammierparadigmen und –sprachen Hinweise zur Vortragstechnik und Erstellung von wissenschaftlichen Artikeln