Computer Science

• Pattern Recognition

  0089bA1.11
  • 19304201 Lecture
    Machine Learning (Tim Landgraf)
    Schedule: Mi 12:00-14:00, Do 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-15)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Additional information / Pre-requisites

    Prerequisites: Basic knowledge  in Mathematics and Algorithms and Data structures.

    Comments

    Contents: Bayesian methods of pattern recognition, clustering, expectation maximization, neuronal networks and learning algorithms, associate networks, recurrent networks. Computer-vision with neuronal networks, applications in Robotics.

    Suggested reading

    wird noch bekannt gegeben

  • 19304202 Practice seminar
    Practice seminar for Pattern recognition / Machine Learning (Manuel Heurich)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-10-20)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

• Project Seminar: Data Management Systems

  0089bA1.13
  • 19303811 Seminar
    Project seminar: Computer science and archaeology (Agnès Voisard)
    Schedule: Do 12:00-14:00 (Class starts on: 2025-10-16)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Requirement

    ALP I-III, Foundations of Datenbase Systems, good programming knowledge.

    Comments

    Research Seminar: Computer Science and Archaeology

    Course Description

    This research seminar brings together students of Informatics and Ancient Studies to explore the application of computational methods to archaeological questions. The research seminar will be a hands-on approach to digital cultural heritage methods, such as spatial analysis, 3D reconstruction, data mining and the digital processing of archaeological artefacts. Examples of datasets will include, but not be limited to, pottery, stone tools, inscriptions, clay tablets, and landscapes.

    A central goal of the seminar is to encourage interdisciplinary collaboration, with students working in pairs — ideally combining a Computer Science student with an Ancient Studies student. Each team will develop and carry out a small research project that combines technical tools with archaeological data, methods, or research questions.

    Topics include, but not limited to:

    – 3D analysis of archaeological artifacts and architecture
    – Geographic Information Systems (GIS) and spatial data analysis
    - Machine learning and computer vision for artifact classification
    – Usage of databases and digital documentation of excavation data
    – OCR/HTR for script in 3D like inscriptions or clay tablets

    Students from Informatics will gain experience applying computational techniques in a humanities context, while students from Ancient Studies will be introduced to digital tools and approaches that support archaeological research.

    No prior coding experience is required for Ancient Studies students, and no background in archaeology is assumed for Computer Science students.

    The seminar is jointly supervised by the Institute of Computer Science and the Archaeoinformatics group of the Institute of Computational Ancient Studies (CompAS) at Freie Universität Berlin, ensuring balanced guidance across disciplines.

    Learning Objectives

    – Understand interdisciplinary challenges and opportunities in digital archaeology

    – Learn to apply and assess computational tools for cultural heritage data

    – Develop and present a collaborative, project-based research outcome

    – Gain insights into current digital humanities and digital archaeology practices

     

     

     

     

    Suggested reading

    Literature and Data Sources:
     

    Open Access if not stated otherwise:

    
    – ACM Journal on Computing and Cultural Heritage
              https://dl.acm.org/journal/jocch
    – De Gruyter Brill on Open Archaeology (OPAR)
              https://www.degruyterbrill.com/journal/key/opar/html
    – Elsevir Journal of Archaeological Science (JAS)
              https://www.sciencedirect.com/journal/journal-of-archaeological-science

    – Journal of Computer Applications in Archaeology (JCAA)
               https://journal.caa-international.org/
    – Journal of Open Archaeological Data (JOAD)
               https://openarchaeologydata.metajnl.com/
    – Journal of Open Humanities Data (JOHD)
               https://openhumanitiesdata.metajnl.com/

    
    Survey articles and Books:
    
    – Advances in digital pottery analysis
              https://doi.org/10.1515/itit-2022-0006
    – Digital Assyriology—Advances in Visual Cuneiform Analysis
              https://doi.org/10.1145/3491239
    – Machine Learning for Ancient Languages: A Survey

              https://doi.org/10.1162/coli_a_00481
    – Airborne laser scanning raster data visualization. A Guide to Good Practice
              https://doi.org/10.3986/9789612549848
    – Digital Humanities, Eine Einführung (German, no Open Acces)
              https://link.springer.com/book/9783476047687
    – New Technologies for Archaeology, Multidisciplinary Investigations in Palpa and Nasca,   Peru (no Open Acces) https://doi.org/10.1007/978-3-540-87438-6
    – Digging in documents: using text mining to access the hidden knowledge in Dutch archaeological excavation reports https://hdl.handle.net/1887/3274287
    
    Databases (related to research partners):

     

    – Heidelberg Objekt- und Multimediadatenbank (HeidICON)
              https://heidicon.ub.uni-heidelberg.de
    – Kooperative Erschließung und Nutzung der Objektdaten von Münzsammlungen
              https://www.kenom.de/
    – Art Institute of Chicago (API)
              https://api.artic.edu/docs/
    – FactGrid, a database for historical research
              https://database.factgrid.de/wiki/Main_Page
    – Research infrastructures of the German Archaeological Institute (DAI), multiple DBs:
              https://idai.world
    – Heidelberg Accession Index (HAI): Zugangsbücher und Bestandsverzeichnisse     deutscher Sammlungen und Museen           https://digi.ub.uni-heidelberg.de/de/hai/index.html

    – Bilddatenbank des Kunsthistorische Instituts (GeschKult, FU)
              https://www.geschkult.fu-berlin.de/e/khi/ressourcen/diathek/digitale_diathek/index.html
    – Epigraphic Database Heidelberg
              https://edh.ub.uni-heidelberg.de/

    – Ubi Erat Lupa  – Bilddatenbank zu antiken Steindenkmälern
              https://lupa.at/
    – Hethitologie-Portal Mainz
              https://hethport.uni-wuerzburg.de
    – Altägyptische Kursivschriften und Digitale Paläographie (AKU-PAL)
              https://aku-pal.uni-mainz.de/graphemes
    – Text Database and Dictionary of Classic Mayan (German and Spanish)
              https://www.classicmayan.org

• Seminar: Contributions to Software Engineering

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  • 19305811 Seminar
    Seminar: Contributions to Software Engineering (Lutz Prechelt)
    Schedule: Do 16:00-18:00 (Class starts on: 2025-10-23)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    Students of Computer Science (also Minor).

    In case you are interested, please contact an adecuate group member with a topic suggestion or request.

    As this lecture is offered continuously, attendance may also start any time during the semester.

    Requirements

    Any computer science student having attended the lecture Software Engineering (Softwaretechnik).

    It may become necessary to deal with materials from the lecture Empirical Evaluation in Informatics (Empirische Bewertung in der Informatik).

    Homepage

    http://www.inf.fu-berlin.de/w/SE/SeminarBeitraegeZumSE

    Comments

    Content

    This is a reseach seminar: normally the presentations are supposed to advance current research projects. Thus, there are, generally speaking, three possible types of topics:

    • published or current research projects from one of the areas in which our software engineering group works
    • especially good specific research projects (or other knowledge) from other areas of software engineering or adjacent areas of computer science
    • basis topics from important areas of software engineering or adjacent disciplines such as psychology, sociology, pedagogics, economics as well as their methods.

    There is no exact restriction of topics though; almost anything is possible.

    Suggested reading

    Je nach Wahl des Vortragsthemas

• Software Project: Web Technologies

  0089bA1.24
  • 19314012 Project Seminar
    Software Project: Semantic Technologies (Adrian Paschke)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-10-15)
    Location: A3/SR 115 (Arnimallee 3-5)
    

    Comments

    Mixed groups of master and bachelor students will either implement an independent project or are part of a larger project in the area of semantic technologies. They will gain in-depth programming knowledge about applications of semantic technologies and artificial intelligence techniques in the Corporate Semantic Web. They will practice teamwork and best practices in software development of large distributed systems and Semantic Web applications. The software project can be done in collaboration with an external partner from industry or standardization. It is possible to continue the project as bachelor or master thesis.

• Software Processes

  0089bA1.25
  • 19306101 Lecture
    Software Processes (Lutz Prechelt)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-10-13)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    The course language is German, but the actual slides and practice sheets are in English.

    The exam will be formulated in German, but answers may be given in English, too.

    Comments

    This course teaches the content of various software development process models, but in particular the power of judgment for deciding which elements of a process may be appropriate or not appropriate and why.

    We discriminate the "classical view" of software engineering (which originates from positivist thinking and the engineering ideals of industrial production) on the one hand and the "modern view" (which originates in humanist thinking and humbler expectations about what engineering should expect to achieve) on the other. We use this discrimination as a litmus test for tracking down cultural undercurrents in software processes that damage a process when and where they are inappropriate for the given task and team.

    For details see the website:https://www.inf.fu-berlin.de/w/SE/VorlesungSoftwareprozesse2025

    Suggested reading

    See the slides

  • 19306102 Practice seminar
    Practice seminar for Software Processes (Lutz Prechelt, Linus Ververs)
    Schedule: Di 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-14)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Comments

    Siehe Vorlesung

• Advanced Topics in Data Management

  0089bA1.26
  • 19304801 Lecture
    Geospatial Databases (Agnès Voisard)
    Schedule: Di 14:00-16:00 (Class starts on: 2025-10-14)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Zielgruppe:
    
    Studierende im Masterstudiengang Voraussetzungen: Vorlesung: Einf. in Datenbanksysteme

    Comments

    The goal of this course is to acquire the background of spatial databases, the kernel of Geographic Systems. The major aspects that will be handled are: modeling and querying geospatial information, spatial access methods (SAMs), data representation, basic operations (mostly from computational geometry), and optimization. Insights into current applications such as location-based services (e.g., navigation systems) will also be given. Knowledge in databases is necessary. This course encompasses: formal lectures, exercises, as well as a practical project with PostGIS.
     

    Suggested reading

    Handouts are enough to understand the course.
    
    The following book will be mostly used: P. Rigaux, M. Scholl, A. Voisard.Spatial Databases - With Application to GIS. Morgan Kaufmann, May 2001. 432 p. (copies in the main library)

  • 19304802 Practice seminar
    Practice seminar for Geospatial Databases (Agnès Voisard)
    Schedule: Do 14:00-16:00 (Class starts on: 2025-10-16)
    Location: A7/SR 031 (Arnimallee 7)
    

• Software Project: Artificial Intelligence

  0089bA1.36
  • 19314012 Project Seminar
    Software Project: Semantic Technologies (Adrian Paschke)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-10-15)
    Location: A3/SR 115 (Arnimallee 3-5)
    

    Comments

    Mixed groups of master and bachelor students will either implement an independent project or are part of a larger project in the area of semantic technologies. They will gain in-depth programming knowledge about applications of semantic technologies and artificial intelligence techniques in the Corporate Semantic Web. They will practice teamwork and best practices in software development of large distributed systems and Semantic Web applications. The software project can be done in collaboration with an external partner from industry or standardization. It is possible to continue the project as bachelor or master thesis.

• Current research topics in Applied Computer Science

  0089cA1.27
  • 19320701 Lecture
    Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 10:00-12:00 (Class starts on: 2025-10-17)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Additional information / Pre-requisites

    The goal of this lecture is to teach principles, methods and tools for the development of secure software applications. To this end, basic concepts are first introduced. This is followed by process models for developing secure software and evaluating the maturity of development processes. Along the phases or process groups of software development, central principles, methods and tools are then introduced and explained. Special attention is given to threat and risk analysis, security requirements, principles and patterns for designing secure software applications, secure and insecure software implementations, security tests and evaluation of the security properties of software applications.

    Comments

    Secure software engineering joins two important fields: Software engineering and information security. software engineering is the systematic use of principles, methods and tools to develop and deploy software. information security covers topics like confidentiality, integrity and availability of informations and data.

    Suggested reading

    - Claudia Eckert: IT-Sicherheit, 11. Auflage, De Gruyter Oldenbourg, 2023; - Ross Anderson: Security Engineering, 3. Auflage, Wiley, 2021. Weitere Literaturhinweise werden zu den einzelnen Themenblöcken bereitgestellt.

  • 19327201 Lecture
    Data compression (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-10-13)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    Data compression is a technology, which only enables a variety of applications in our information age. Even though the underlying technology is often hidden from the end user, we use data compression every day when we hear music, watch images and videos, or use applications on our smartphone.

    In this course, the fundamental and most often used approaches for data compression are introduced.  We discuss theoretical foundations as well as methods used in practice.

    The first part of the course deals with lossless compression, in which the original data can be reconstructed exactly. This part includes the following topics:

    • Unique decodability and prefix codes
    • Entropy and entropy rate as theoretical limits of lossless compression
    • Optimal codes, Huffman codes
    • Arithmetic coding
    • Lempel-Ziv coding
    • Linear prediction
    • Examples from text, image and audio compression

    In the second part of the course, we consider lossy compression, by which only an approximation of the original data can be reconstructed. This type of compression enables much higher compression rates and is the dominant form of compression for audio, image and video data. The second part of the course includes the following topics:

    • Scalar quantization, optimal scalar quantization
    • Theoretical limits of lossy compression: Rate distortion functions
    • Vector quantization
    • Predictive quantization
    • Transform coding
    • Examples from audio, image, and video compression

    Suggested reading

    • Sayood, K. (2018), “Introduction to Data Compression,” Morgan Kaufmann, Cambridge, MA.
    • Cover, T. M. and Thomas, J. A. (2006), “Elements of Information Theory,” John Wiley & Sons, New York.
    • Gersho, A. and Gray, R. M. (1992), “Vector Quantization and Signal Compression,” Kluwer Academic Publishers, Boston, Dordrecht, London.
    • Jayant, N. S. and Noll, P. (1994), “Digital Coding of Waveforms,” Prentice-Hall, Englewood Cliffs, NJ, USA.
    • Wiegand, T. and Schwarz, H. (2010), “Source Coding: Part I of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, vol. 4, no. 1-2.

  • 19328301 Lecture
    Data Visualization (Claudia Müller-Birn)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Link to the course on the HCC-Website: https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/winter_term_2025_26/course_data_visualization.html

    Comments

    The current rapid technological development requires the processing of large amounts of data of various kinds to make them usable by humans. This challenge affects many areas of life today, such as research, business, and politics. In these contexts, decision-makers use data visualizations to explain information and its relationships through graphical representations of data. This course aims to familiarize students with the principles, techniques, and methods in data visualization and provide practical skills for designing and implementing data visualizations.

    This course gives students a solid introduction to the fundamentals of data visualization with current insights from research and practice. By the end of the course, students will

    1. Be able to select and apply methods for designing visualizations based on a problem,
    2. know essential theoretical basics of visualization for graphical perception and cognition,
    3. know and be able to select visualization approaches and their advantages and disadvantages,
    4. be able to evaluate visualization solutions critically, and
    5. have acquired practical skills for implementing visualizations.

    This course is intended for students interested in using data visualization in their work and students who want to develop visualization software. Basic knowledge of programming (HTML, CSS, Javascript, Python) and data analysis (e.g., R) is helpful.

    In addition to participating in class discussions, students will complete several programming and data analysis assignments. In a mini-project, students work on a given problem. Finally, we expect students to document and present their assignments and mini-project in a reproducible manner.

    Please note that the course will focus on how data is visually coded and presented for analysis after the data structure and its content are known. We do not cover exploratory analysis methods for discovering insights in data are not the focus of the course.

    Suggested reading

    Textbook

    Munzner, Tamara. Visualization analysis and design. AK Peters/CRC Press, 2014.

    Additional Literature

    Kirk, Andy: Data visualisation: A handbook for data driven design. Sage. 2016.

    Yau, Nathan: Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. Wiley Publishing, Inc. 2011.

    Spence, Robert: Information Visualization: Design for Interaction. Pearson. 2007.

  • 19328601 Lecture
    Kryptowährungen und Blockchain (Katinka Wolter)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: , T9/051 Seminarraum
    

    Comments

    We will study the history, technology and applications of cryptocurrencies and blockchain.

    Suggested reading

    Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction, by Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, Steven Goldfeder

  • 19334301 Lecture
    Advanced Robotics (Daniel Göhring)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-10-15)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    The lecture "Advanced Robotics" complements the lecture "Introduction to Robotics" and is for students who are familiar with basic concepts of robotics and the robot operating system ROS. Algorithms will be implemented in ROS using real data from autonomous vehicles and via written examples.

    The following topics will be covered (variations are possible):

    • Coordinate Systems, Representations, Kinematic Chains
    • Denavit Hartenberg 
    • Jacobian Matrix and Inverse Kinematics
    • Particle Filters
    • Simultaneous localization and mapping
    • Splines
    • Hierarchical Planning
    • ARA, D*, probabilistic planners
    • Reinforcement Learning
    • Model Predictive Control
    • Stereo Matching with SIFT-Features and Ransac 
    • Semi-global Matching
    • Visual Odometry / Optical Flow

  • 19320702 Practice seminar
    Practice seminar for Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 12:00-14:00 (Class starts on: 2025-10-17)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19327202 Practice seminar
    Practice seminar for Data Compression (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2025-10-13)
    Location: T9/046 Seminarraum (Takustr. 9)
    
  • 19328302 Practice seminar
    Data Visualization (Malte Heiser)
    Schedule: Do 08:00-10:00, Do 10:00-12:00 (Class starts on: 2025-10-16)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19328602 Practice seminar
    Practice Session on Cryptocurrencies (Justus Purat)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-10-16)
    Location: T9/051 Seminarraum (Takustr. 9)
    
  • 19334302 Practice seminar
    Practice Seminar for Advanced Robotics (Daniel Göhring)
    Schedule: Do 12:00-14:00 (Class starts on: 2025-10-16)
    Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
    

• Special Aspects of Applied Computer Science

  0089cA1.28
  • 19320701 Lecture
    Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 10:00-12:00 (Class starts on: 2025-10-17)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Additional information / Pre-requisites

    The goal of this lecture is to teach principles, methods and tools for the development of secure software applications. To this end, basic concepts are first introduced. This is followed by process models for developing secure software and evaluating the maturity of development processes. Along the phases or process groups of software development, central principles, methods and tools are then introduced and explained. Special attention is given to threat and risk analysis, security requirements, principles and patterns for designing secure software applications, secure and insecure software implementations, security tests and evaluation of the security properties of software applications.

    Comments

    Secure software engineering joins two important fields: Software engineering and information security. software engineering is the systematic use of principles, methods and tools to develop and deploy software. information security covers topics like confidentiality, integrity and availability of informations and data.

    Suggested reading

    - Claudia Eckert: IT-Sicherheit, 11. Auflage, De Gruyter Oldenbourg, 2023; - Ross Anderson: Security Engineering, 3. Auflage, Wiley, 2021. Weitere Literaturhinweise werden zu den einzelnen Themenblöcken bereitgestellt.

  • 19327201 Lecture
    Data compression (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-10-13)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    Data compression is a technology, which only enables a variety of applications in our information age. Even though the underlying technology is often hidden from the end user, we use data compression every day when we hear music, watch images and videos, or use applications on our smartphone.

    In this course, the fundamental and most often used approaches for data compression are introduced.  We discuss theoretical foundations as well as methods used in practice.

    The first part of the course deals with lossless compression, in which the original data can be reconstructed exactly. This part includes the following topics:

    • Unique decodability and prefix codes
    • Entropy and entropy rate as theoretical limits of lossless compression
    • Optimal codes, Huffman codes
    • Arithmetic coding
    • Lempel-Ziv coding
    • Linear prediction
    • Examples from text, image and audio compression

    In the second part of the course, we consider lossy compression, by which only an approximation of the original data can be reconstructed. This type of compression enables much higher compression rates and is the dominant form of compression for audio, image and video data. The second part of the course includes the following topics:

    • Scalar quantization, optimal scalar quantization
    • Theoretical limits of lossy compression: Rate distortion functions
    • Vector quantization
    • Predictive quantization
    • Transform coding
    • Examples from audio, image, and video compression

    Suggested reading

    • Sayood, K. (2018), “Introduction to Data Compression,” Morgan Kaufmann, Cambridge, MA.
    • Cover, T. M. and Thomas, J. A. (2006), “Elements of Information Theory,” John Wiley & Sons, New York.
    • Gersho, A. and Gray, R. M. (1992), “Vector Quantization and Signal Compression,” Kluwer Academic Publishers, Boston, Dordrecht, London.
    • Jayant, N. S. and Noll, P. (1994), “Digital Coding of Waveforms,” Prentice-Hall, Englewood Cliffs, NJ, USA.
    • Wiegand, T. and Schwarz, H. (2010), “Source Coding: Part I of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, vol. 4, no. 1-2.

  • 19328301 Lecture
    Data Visualization (Claudia Müller-Birn)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Link to the course on the HCC-Website: https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/winter_term_2025_26/course_data_visualization.html

    Comments

    The current rapid technological development requires the processing of large amounts of data of various kinds to make them usable by humans. This challenge affects many areas of life today, such as research, business, and politics. In these contexts, decision-makers use data visualizations to explain information and its relationships through graphical representations of data. This course aims to familiarize students with the principles, techniques, and methods in data visualization and provide practical skills for designing and implementing data visualizations.

    This course gives students a solid introduction to the fundamentals of data visualization with current insights from research and practice. By the end of the course, students will

    1. Be able to select and apply methods for designing visualizations based on a problem,
    2. know essential theoretical basics of visualization for graphical perception and cognition,
    3. know and be able to select visualization approaches and their advantages and disadvantages,
    4. be able to evaluate visualization solutions critically, and
    5. have acquired practical skills for implementing visualizations.

    This course is intended for students interested in using data visualization in their work and students who want to develop visualization software. Basic knowledge of programming (HTML, CSS, Javascript, Python) and data analysis (e.g., R) is helpful.

    In addition to participating in class discussions, students will complete several programming and data analysis assignments. In a mini-project, students work on a given problem. Finally, we expect students to document and present their assignments and mini-project in a reproducible manner.

    Please note that the course will focus on how data is visually coded and presented for analysis after the data structure and its content are known. We do not cover exploratory analysis methods for discovering insights in data are not the focus of the course.

    Suggested reading

    Textbook

    Munzner, Tamara. Visualization analysis and design. AK Peters/CRC Press, 2014.

    Additional Literature

    Kirk, Andy: Data visualisation: A handbook for data driven design. Sage. 2016.

    Yau, Nathan: Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. Wiley Publishing, Inc. 2011.

    Spence, Robert: Information Visualization: Design for Interaction. Pearson. 2007.

  • 19328601 Lecture
    Kryptowährungen und Blockchain (Katinka Wolter)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: , T9/051 Seminarraum
    

    Comments

    We will study the history, technology and applications of cryptocurrencies and blockchain.

    Suggested reading

    Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction, by Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, Steven Goldfeder

  • 19334301 Lecture
    Advanced Robotics (Daniel Göhring)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-10-15)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    The lecture "Advanced Robotics" complements the lecture "Introduction to Robotics" and is for students who are familiar with basic concepts of robotics and the robot operating system ROS. Algorithms will be implemented in ROS using real data from autonomous vehicles and via written examples.

    The following topics will be covered (variations are possible):

    • Coordinate Systems, Representations, Kinematic Chains
    • Denavit Hartenberg 
    • Jacobian Matrix and Inverse Kinematics
    • Particle Filters
    • Simultaneous localization and mapping
    • Splines
    • Hierarchical Planning
    • ARA, D*, probabilistic planners
    • Reinforcement Learning
    • Model Predictive Control
    • Stereo Matching with SIFT-Features and Ransac 
    • Semi-global Matching
    • Visual Odometry / Optical Flow

  • 19320702 Practice seminar
    Practice seminar for Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 12:00-14:00 (Class starts on: 2025-10-17)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19327202 Practice seminar
    Practice seminar for Data Compression (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2025-10-13)
    Location: T9/046 Seminarraum (Takustr. 9)
    
  • 19328302 Practice seminar
    Data Visualization (Malte Heiser)
    Schedule: Do 08:00-10:00, Do 10:00-12:00 (Class starts on: 2025-10-16)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19328602 Practice seminar
    Practice Session on Cryptocurrencies (Justus Purat)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-10-16)
    Location: T9/051 Seminarraum (Takustr. 9)
    
  • 19334302 Practice seminar
    Practice Seminar for Advanced Robotics (Daniel Göhring)
    Schedule: Do 12:00-14:00 (Class starts on: 2025-10-16)
    Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
    

• Special Aspects of Software Development

  0089cA1.30
  • 19320701 Lecture
    Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 10:00-12:00 (Class starts on: 2025-10-17)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Additional information / Pre-requisites

    The goal of this lecture is to teach principles, methods and tools for the development of secure software applications. To this end, basic concepts are first introduced. This is followed by process models for developing secure software and evaluating the maturity of development processes. Along the phases or process groups of software development, central principles, methods and tools are then introduced and explained. Special attention is given to threat and risk analysis, security requirements, principles and patterns for designing secure software applications, secure and insecure software implementations, security tests and evaluation of the security properties of software applications.

    Comments

    Secure software engineering joins two important fields: Software engineering and information security. software engineering is the systematic use of principles, methods and tools to develop and deploy software. information security covers topics like confidentiality, integrity and availability of informations and data.

    Suggested reading

    - Claudia Eckert: IT-Sicherheit, 11. Auflage, De Gruyter Oldenbourg, 2023; - Ross Anderson: Security Engineering, 3. Auflage, Wiley, 2021. Weitere Literaturhinweise werden zu den einzelnen Themenblöcken bereitgestellt.

  • 19335201 Lecture
    Cybersecurity and AI III (Gerhard Wunder)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    
  • 19320702 Practice seminar
    Practice seminar for Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 12:00-14:00 (Class starts on: 2025-10-17)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19335202 Practice seminar
    Practice seminar for Cybersecurity and AI III (Gerhard Wunder)
    Schedule: Fr 12:00-14:00 (Class starts on: 2025-10-17)
    Location: A7/SR 031 (Arnimallee 7)
    

• Advanced Algorithms

  0089cA2.1
  • 19303501 Lecture
    Advanced Algorithms (Helmut Alt)
    Schedule: Mo 10:00-12:00, Fr 10:00-12:00 (Class starts on: 2025-10-13)
    Location: KöLu24-26/SR 006 Neuro/Mathe (Königin-Luise-Str. 24 / 26)
    

    Additional information / Pre-requisites

    Target audience

    All Master and Bachelor students who are interested in algorithms.

    Prerequisites

    Basic familiarity with the design and analysis of algorithms.

    Comments

    The class focuses on topics such as

    • general principles of algorithm design,
    • network flows,
    • number-theoretic algorithms (including the RSA crypto system),
    • string matching,
    • NP-completeness,
    • approximation algorithms for hard problems,
    • arithmetic algorithms and circuits, fast fourier transform.

    Suggested reading

    • Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms, 2nd Ed. McGraw-Hill 2001
    • Kleinberg, Tardos: Algorithm Design Addison-Wesley 2005.

  • 19303502 Practice seminar
    Practice seminar for Advanced Algorithms (Helmut Alt)
    Schedule: Mi 08:00-10:00, Mi 14:00-16:00 (Class starts on: 2025-10-15)
    Location: T9/046 Seminarraum (Takustr. 9)
    

• Current Research Topics in Theoretical Computer Science

  0089cA2.3
  • 19320501 Lecture
    Quantenalgorithm and Cryptanalysis (Marian Margraf)
    Schedule: Di 10:00-12:00 (Class starts on: 2025-10-14)
    Location: A7/SR 140 Seminarraum (Hinterhaus) (Arnimallee 7)
    

    Comments

    The lecture aims at a deeper understanding of cryptographic algorithms, especially which design criteria have to be considered for the development of secure encryption algorithms. For that purpose we will get to know and evaluate different cryptanalytic methods for symmetrical and asymmetrical encryption techniques – e.g. linear and differential cryptanalysis on block ciphers, correlation attacks on stream ciphers and algorithms to solve the factorization problem and the discrete logarithm problem. Weaknesses in the implementation, e.g. to exploit side-channel attacks, will be discussed only peripherally.

  • 19337401 Lecture
    Post Quantum Cryptography - the NIST algorithms (N.N.)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-10-15)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Comments

    Post Quantum Cryptography - the NIST algorithms

    Course description:
    This course provides an in-depth study of the post-quantum cryptographic algorithms selected and evaluated by NIST. Students will explore the foundational mathematics, security assumptions, algorithmic designs, and practical implementation issues of cryptographic systems believed to be secure against quantum adversaries. Emphasis is placed on NIST's selected algorithms: KYBER (KEM), DILITHIUM (signatures), and SPHINCS+(stateless signatures), as well as alternate schemes such as Classic McEliece, BIKE, HQC, and Falcon.

    Learning Objectives:
    By the end of this course, students will be able to:

    • Describe the threat quantum computing poses to classical cryptography.
    • Explain the design principles of hash-based, code-based, multivariate, and lattice-based cryptography.
    • Analyze the security assumptions behind each NIST PQC algorithm family.
    • Compare performance and implementation trade-offs among leading PQC schemes.
    • Evaluate real-world deployment strategies and limitations for PQC.

     

  • 19320502 Practice seminar
    Practice seminar for Cryptanalysis (Marian Margraf)
    Schedule: Mi 12:00-14:00 (Class starts on: 2025-10-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    
  • 19337402 Practice seminar
    Tutorials for Post Quantum Cryptography - the NIST algorithms (N.N.)
    Schedule: Fr 08:00-10:00 (Class starts on: 2025-10-17)
    Location: T9/051 Seminarraum (Takustr. 9)
    

• Special aspects of Theoretical Computer Science

  0089cA2.7
  • 19320501 Lecture
    Quantenalgorithm and Cryptanalysis (Marian Margraf)
    Schedule: Di 10:00-12:00 (Class starts on: 2025-10-14)
    Location: A7/SR 140 Seminarraum (Hinterhaus) (Arnimallee 7)
    

    Comments

    The lecture aims at a deeper understanding of cryptographic algorithms, especially which design criteria have to be considered for the development of secure encryption algorithms. For that purpose we will get to know and evaluate different cryptanalytic methods for symmetrical and asymmetrical encryption techniques – e.g. linear and differential cryptanalysis on block ciphers, correlation attacks on stream ciphers and algorithms to solve the factorization problem and the discrete logarithm problem. Weaknesses in the implementation, e.g. to exploit side-channel attacks, will be discussed only peripherally.

  • 19327201 Lecture
    Data compression (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-10-13)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    Data compression is a technology, which only enables a variety of applications in our information age. Even though the underlying technology is often hidden from the end user, we use data compression every day when we hear music, watch images and videos, or use applications on our smartphone.

    In this course, the fundamental and most often used approaches for data compression are introduced.  We discuss theoretical foundations as well as methods used in practice.

    The first part of the course deals with lossless compression, in which the original data can be reconstructed exactly. This part includes the following topics:

    • Unique decodability and prefix codes
    • Entropy and entropy rate as theoretical limits of lossless compression
    • Optimal codes, Huffman codes
    • Arithmetic coding
    • Lempel-Ziv coding
    • Linear prediction
    • Examples from text, image and audio compression

    In the second part of the course, we consider lossy compression, by which only an approximation of the original data can be reconstructed. This type of compression enables much higher compression rates and is the dominant form of compression for audio, image and video data. The second part of the course includes the following topics:

    • Scalar quantization, optimal scalar quantization
    • Theoretical limits of lossy compression: Rate distortion functions
    • Vector quantization
    • Predictive quantization
    • Transform coding
    • Examples from audio, image, and video compression

    Suggested reading

    • Sayood, K. (2018), “Introduction to Data Compression,” Morgan Kaufmann, Cambridge, MA.
    • Cover, T. M. and Thomas, J. A. (2006), “Elements of Information Theory,” John Wiley & Sons, New York.
    • Gersho, A. and Gray, R. M. (1992), “Vector Quantization and Signal Compression,” Kluwer Academic Publishers, Boston, Dordrecht, London.
    • Jayant, N. S. and Noll, P. (1994), “Digital Coding of Waveforms,” Prentice-Hall, Englewood Cliffs, NJ, USA.
    • Wiegand, T. and Schwarz, H. (2010), “Source Coding: Part I of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, vol. 4, no. 1-2.

  • 19335201 Lecture
    Cybersecurity and AI III (Gerhard Wunder)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    
  • 19337401 Lecture
    Post Quantum Cryptography - the NIST algorithms (N.N.)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-10-15)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Comments

    Post Quantum Cryptography - the NIST algorithms

    Course description:
    This course provides an in-depth study of the post-quantum cryptographic algorithms selected and evaluated by NIST. Students will explore the foundational mathematics, security assumptions, algorithmic designs, and practical implementation issues of cryptographic systems believed to be secure against quantum adversaries. Emphasis is placed on NIST's selected algorithms: KYBER (KEM), DILITHIUM (signatures), and SPHINCS+(stateless signatures), as well as alternate schemes such as Classic McEliece, BIKE, HQC, and Falcon.

    Learning Objectives:
    By the end of this course, students will be able to:

    • Describe the threat quantum computing poses to classical cryptography.
    • Explain the design principles of hash-based, code-based, multivariate, and lattice-based cryptography.
    • Analyze the security assumptions behind each NIST PQC algorithm family.
    • Compare performance and implementation trade-offs among leading PQC schemes.
    • Evaluate real-world deployment strategies and limitations for PQC.

     

  • 19320502 Practice seminar
    Practice seminar for Cryptanalysis (Marian Margraf)
    Schedule: Mi 12:00-14:00 (Class starts on: 2025-10-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    
  • 19327202 Practice seminar
    Practice seminar for Data Compression (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2025-10-13)
    Location: T9/046 Seminarraum (Takustr. 9)
    
  • 19335202 Practice seminar
    Practice seminar for Cybersecurity and AI III (Gerhard Wunder)
    Schedule: Fr 12:00-14:00 (Class starts on: 2025-10-17)
    Location: A7/SR 031 (Arnimallee 7)
    
  • 19337402 Practice seminar
    Tutorials for Post Quantum Cryptography - the NIST algorithms (N.N.)
    Schedule: Fr 08:00-10:00 (Class starts on: 2025-10-17)
    Location: T9/051 Seminarraum (Takustr. 9)
    

• Cryptography and Security in Distributed Systems

  0089cA2.8
  • 19303601 Lecture
    Cryptography and Security in Distributed Systems (Volker Roth)
    Schedule: Mi 14:00-16:00, Do 10:00-12:00 (Class starts on: 2025-10-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Requirements: Participants must have a good mathematical understanding and good knowledge of computer security and networking.

    Comments

    This course gives an introduction to cryptography and cryptographic key management, as well as an introduction to cryptographic protocols and their application in the field of security in distributed systems. Relevant mathematical tools will be developed accordingly. In addition, the lecture addresses the importance of implementation details in the context of IT system security.

    Suggested reading

    • Jonathan Katz and Yehuda Lindell, Introduction to Modern Cryptography, 2008
    • Lindsay N. Childs, A Concrete Introduction to Higher Algebra. Springer Verlag, 1995.
    • Johannes Buchmann, Einfuehrung in die Kryptographie. Springer Verlag, 1999.

    Weitere noch zu bestimmende Literatur und Primärquellen.

  • 19303602 Practice seminar
    Übung zu Kryptographie und Sicherheit in Verteilten Systemen (Volker Roth)
    Schedule: Do 14:00-16:00 (Class starts on: 2025-10-16)
    Location: , T9/049 Seminarraum
    

• Operating Systems

  0089cA3.1
  • 19312101 Lecture
    Systems Software (Barry Linnert)
    Schedule: Di 12:00-14:00, Mi 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-14)
    Location: A7/SR 031 (Arnimallee 7)
    

    Additional information / Pre-requisites

    Language

    The course language is German as is the oral presentation of the lecturer, but the slides and all written material is available in English. You can always ask questions in English. The practice sheets and final exam are formulated in German as well as in English.

    Homepage

    https://www.inf.fu-berlin.de/w/SE/VorlesungBetriebssysteme2025

    Comments

    Operating systems tie together the execution of applications, user experience and usability with the management of computer hardware. Starting with the tasks an operating system has to perform and the requirements it has to meet, the most important aspects of design and development of modern operating systems will be introduced:

    • Structure and design of an operating system including historical summary, structures and philosophies of OS design and resources and resource management
    • Threads and processes including thread management
    • Scheduling including real-time scheduling
    • Process interaction and inter-process communication
    • Resource management including device operation, driver development, management and operation of input- and output devices
    • Memory management including address spaces and virtual memory
    • File system including management and operation of discs and memory hierarchy
    • Distributed operating systems including distributed architectures for resource management
    • Performance evaluation and modeling including overload detection and handling

    Modern operating systems provide examples for different aspects and current research will be introduced. The tutorials serve to reflect the topics dealt with in the lecture and to acquire experience by developing a small operating system.

    Suggested reading

    • A.S. Tanenbaum: Modern Operating Systems, 2nd Ed. Prentice-Hall, 2001
    • A. Silberschatz et al.: Operating Systems Concepts with Java, 6th Ed. Wiley, 2004

  • 19312102 Practice seminar
    Practice seminar for Systems Software (Barry Linnert)
    Schedule: Do 14:00-16:00 (Class starts on: 2025-10-16)
    Location: T9/046 Seminarraum (Takustr. 9)
    

• Current Research Topics in Computer Systems

  0089cA3.10
  • 19328601 Lecture
    Kryptowährungen und Blockchain (Katinka Wolter)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: , T9/051 Seminarraum
    

    Comments

    We will study the history, technology and applications of cryptocurrencies and blockchain.

    Suggested reading

    Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction, by Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, Steven Goldfeder

  • 19334301 Lecture
    Advanced Robotics (Daniel Göhring)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-10-15)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    The lecture "Advanced Robotics" complements the lecture "Introduction to Robotics" and is for students who are familiar with basic concepts of robotics and the robot operating system ROS. Algorithms will be implemented in ROS using real data from autonomous vehicles and via written examples.

    The following topics will be covered (variations are possible):

    • Coordinate Systems, Representations, Kinematic Chains
    • Denavit Hartenberg 
    • Jacobian Matrix and Inverse Kinematics
    • Particle Filters
    • Simultaneous localization and mapping
    • Splines
    • Hierarchical Planning
    • ARA, D*, probabilistic planners
    • Reinforcement Learning
    • Model Predictive Control
    • Stereo Matching with SIFT-Features and Ransac 
    • Semi-global Matching
    • Visual Odometry / Optical Flow

  • 19335201 Lecture
    Cybersecurity and AI III (Gerhard Wunder)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    
  • 19328602 Practice seminar
    Practice Session on Cryptocurrencies (Justus Purat)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-10-16)
    Location: T9/051 Seminarraum (Takustr. 9)
    
  • 19334302 Practice seminar
    Practice Seminar for Advanced Robotics (Daniel Göhring)
    Schedule: Do 12:00-14:00 (Class starts on: 2025-10-16)
    Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
    
  • 19335202 Practice seminar
    Practice seminar for Cybersecurity and AI III (Gerhard Wunder)
    Schedule: Fr 12:00-14:00 (Class starts on: 2025-10-17)
    Location: A7/SR 031 (Arnimallee 7)
    

• Special Aspects of Computer Systems

  0089cA3.11
  • 19327201 Lecture
    Data compression (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-10-13)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    Data compression is a technology, which only enables a variety of applications in our information age. Even though the underlying technology is often hidden from the end user, we use data compression every day when we hear music, watch images and videos, or use applications on our smartphone.

    In this course, the fundamental and most often used approaches for data compression are introduced.  We discuss theoretical foundations as well as methods used in practice.

    The first part of the course deals with lossless compression, in which the original data can be reconstructed exactly. This part includes the following topics:

    • Unique decodability and prefix codes
    • Entropy and entropy rate as theoretical limits of lossless compression
    • Optimal codes, Huffman codes
    • Arithmetic coding
    • Lempel-Ziv coding
    • Linear prediction
    • Examples from text, image and audio compression

    In the second part of the course, we consider lossy compression, by which only an approximation of the original data can be reconstructed. This type of compression enables much higher compression rates and is the dominant form of compression for audio, image and video data. The second part of the course includes the following topics:

    • Scalar quantization, optimal scalar quantization
    • Theoretical limits of lossy compression: Rate distortion functions
    • Vector quantization
    • Predictive quantization
    • Transform coding
    • Examples from audio, image, and video compression

    Suggested reading

    • Sayood, K. (2018), “Introduction to Data Compression,” Morgan Kaufmann, Cambridge, MA.
    • Cover, T. M. and Thomas, J. A. (2006), “Elements of Information Theory,” John Wiley & Sons, New York.
    • Gersho, A. and Gray, R. M. (1992), “Vector Quantization and Signal Compression,” Kluwer Academic Publishers, Boston, Dordrecht, London.
    • Jayant, N. S. and Noll, P. (1994), “Digital Coding of Waveforms,” Prentice-Hall, Englewood Cliffs, NJ, USA.
    • Wiegand, T. and Schwarz, H. (2010), “Source Coding: Part I of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, vol. 4, no. 1-2.

  • 19328601 Lecture
    Kryptowährungen und Blockchain (Katinka Wolter)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: , T9/051 Seminarraum
    

    Comments

    We will study the history, technology and applications of cryptocurrencies and blockchain.

    Suggested reading

    Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction, by Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, Steven Goldfeder

  • 19334301 Lecture
    Advanced Robotics (Daniel Göhring)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-10-15)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    The lecture "Advanced Robotics" complements the lecture "Introduction to Robotics" and is for students who are familiar with basic concepts of robotics and the robot operating system ROS. Algorithms will be implemented in ROS using real data from autonomous vehicles and via written examples.

    The following topics will be covered (variations are possible):

    • Coordinate Systems, Representations, Kinematic Chains
    • Denavit Hartenberg 
    • Jacobian Matrix and Inverse Kinematics
    • Particle Filters
    • Simultaneous localization and mapping
    • Splines
    • Hierarchical Planning
    • ARA, D*, probabilistic planners
    • Reinforcement Learning
    • Model Predictive Control
    • Stereo Matching with SIFT-Features and Ransac 
    • Semi-global Matching
    • Visual Odometry / Optical Flow

  • 19335201 Lecture
    Cybersecurity and AI III (Gerhard Wunder)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    
  • 19327202 Practice seminar
    Practice seminar for Data Compression (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2025-10-13)
    Location: T9/046 Seminarraum (Takustr. 9)
    
  • 19328602 Practice seminar
    Practice Session on Cryptocurrencies (Justus Purat)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-10-16)
    Location: T9/051 Seminarraum (Takustr. 9)
    
  • 19334302 Practice seminar
    Practice Seminar for Advanced Robotics (Daniel Göhring)
    Schedule: Do 12:00-14:00 (Class starts on: 2025-10-16)
    Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
    
  • 19335202 Practice seminar
    Practice seminar for Cybersecurity and AI III (Gerhard Wunder)
    Schedule: Fr 12:00-14:00 (Class starts on: 2025-10-17)
    Location: A7/SR 031 (Arnimallee 7)
    

• Microprocessor Lab

  0089cA3.2
  • 19310030 Internship
    Practical Project: Microprocessors (Larissa Groth)
    Schedule: Di 14:00-16:00, Mi 12:00-14:00, Fr 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-14)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Additional information / Pre-requisites

    Important information about the course:
    The microprocessor practical course will be offered this semester with a joint theory session on Fridays, 2-4 p.m., and two independent practical exercise sessions:

    • Group A, Tuesdays, 2-4 p.m. Takustraße 9, Room K63
    • Group B, Wednesdays, 12-2 p.m. Takustraße 9, Room K63

    One of these practice dates must be chosen.

    Comments

    ATTENTION: Contrary to the schedule in the course catalog, this course does not have 3 mandatory dates, but only 2! See below for further information!

    The overwhelming majority of future computer systems will be characterized by communicating, embedded systems. These are found in machine controls, household appliances, motor vehicles, airplanes, intelligent buildings, etc. and will in future be increasingly integrated into networks such as the Internet.

    The internship will address the architecture of embedded systems and demonstrate the differences to traditional PC architectures (e.g., real-time capability, interaction with the environment) with practical examples. The internship is based on 16- and 32-bit microcontroller systems.

    The main focus of the internship is the following:

    •     register structures
    •     memory organization
    •     Hardware assembler and high-language programming
    •     I / O system and timer programming
    •     Interrupt system
    •     Watchdog logic
    •     Analog interface
    •     Bus system connection of components
    •     Communication (serial, CAN bus, Ethernet, radio and USB)
    •     Control of models and use of different sensors

    Suggested reading

    • Brian W. Kernighan, Dennis M. Ritchie: The C Programming Language, Second Edition, Prentice Hall, 1988.

• Telematics

  0089cA3.5
  • 19305101 Lecture
    Telematics (Jochen Schiller)
    Schedule: Mo 14:00-16:00, Fr 14:00-16:00 (Class starts on: 2025-10-13)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Requirements: Basic understanding of computer networks, e.g., TI-III

     

    Comments

    Content

    Telematics = telecommunications + informatics (often also called computer networks) covers a wide spectrum of topics - from communication engineering to the WWW and advanced applications.

    The lecture addresses topics such as:

    • Basic background: protocols, services, models, communication standards;
    • Principles of communication engineering: signals, coding, modulation, media;
    • Data link layer: media access etc.;
    • Local networks: IEEE-Standards, Ethernet, bridges;
    • Network layer: routing and forwarding, Internet protocols (IPv4, IPv6);
    • Transport layer: quality of service, flow control, congestion control, TCP;
    • Internet: TCP/IP protocol suite;
    • Applications: WWW, security, network management;
    • New network concepts (QUIC etc.).

    At the End of this course, you should...

    • know how networks in general are organized
    • know what the Internet could be or is
    • understand how wired/wireless (see Mobile Communications) networks work
    • understand why/how protocols and layers are used
    • understand how e-mails, videos get to where you are
    • understand how operators operate real, big networks
    • understand the cooperation of web browsers with web servers
    • be aware of security issues when you use the network
    • be familiar with acronyms like: ALOHA, ARP, ATM, BGP, CDMA, CDN, CIDR, CSMA, DCCP, DHCP, ETSI, FDM, FDMA, FTP, HDLC, HTTP, ICMP, ICN, IEEE, IETF, IP, IMAP, ISP, ITU, ISO/OSI, LAN, LTE, MAC, MAN, MPLS, MTU, NAT, NTP, PCM, POTS, PPP, PSTN, P2P, QUIC, RARP, SCTP, SMTP, SNMP, TCP, TDM, TDMA, UDP, UMTS, VPN, WAN, ...

    Literature

    • A. Tanenbaum & D. Wetherall: Computer Networks (5th edition)
    • J. Kurose & K. Ross: Computer Networking (6th edition)
    • S. Keshav: Mathematical Foundations of Computer Networking (2012)
    • W. Stallings book, W. Goralski book 
    • IETF drafts and RFCs
    • IEEE 802 LAN/MAN standards

    Prerequisites

    As this is a Master Course you have to know the basics of computer networks already (e.g. from the OS&CN BSc course or any other basic networking course). That means you know what protocol stacks are, know the basic ideas behind TCP/IP, know layering principles, got a rough understanding of how the Internet works. This course will recap the basics but then proceed to the more advanced stuff.

    Resources & Organization

    The course comprises about 30 "lectures", 90 minutes each, following the inverted or flipped classroom principle. I.e. you will be able to access a video of the lecture before we discuss the content in class. To be able to discuss you have to watch the video BEFORE we meet! This is your main assignment - go through the video, prepare questions if something is not clear. During the meetings there will be a recap of the main ideas plus enough time to discuss each topic if necessary.

    Suggested reading

    • Larry Peterson, Bruce S. Davie: Computernetze - Ein modernes Lehrbuch, dpunkt Verlag, Heidelberg, 2000
    • Krüger, G., Reschke, D.: Lehr- und Übungsbuch Telematik, Fachbuchverlag Leipzig, 2000
    • Kurose, J. F., Ross, K. W.: Computer Networking: A Top-Down Approach Featuring the Internet, Addi-son-Wesley Publishing Company, Wokingham, England, 2001
    • Siegmund, G.: Technik der Netze, 4. Auflage, Hüthig Verlag, Heidelberg, 1999
    • Halsall, F.: Data Communi-cations, Computer Networks and Open Systems 4. Auflage, Addison-Wesley Publishing Company, Wokingham, England, 1996
    • Tanenbaum, A. S.: Computer Networks, 3. Auflage, Prentice Hall, Inc., New Jersey, 1996

  • 19305102 Practice seminar
    Practice seminar for Telematics (Jochen Schiller, Marius Max Wawerek)
    Schedule: Mo 16:00-18:00 (Class starts on: 2025-10-20)
    Location: T9/055 Seminarraum (Takustr. 9)
    

• Numerical Mathematics I

  0084cA1.9
  • 19212001 Lecture
    Numerics I (Volker John)
    Schedule: Mo 10:00-12:00, Mi 10:00-12:00 (Class starts on: 2025-10-13)
    Location: A7/SR 031 (Arnimallee 7)
    

    Comments

    Numerical methods for: iterative solution of nonlinear systems of equations (fixpoint and Newton methods), curve fitting, interpolation, numerical quadrature, and numerics for initial value problems and two point boundary value problems with ODEs. The course is taught in German.

    Suggested reading

    Stoer, Josef und Roland Bulirsch: Numerische Mathematik - eine Einführung, Band 1. Springer, Berlin, 2005.

    Aus dem FU-Netz auch online verfügbar.

    Es wird ein Vorlesungsskript geben.

    Link

  • 19212002 Practice seminar
    Practice seminar for Numerics I (N.N.)
    Schedule: Di 10:00-12:00, Di 12:00-14:00 (Class starts on: 2025-10-14)
    Location: A3/SR 120 (Arnimallee 3-5)
    

• Algebra and Number Theory

  0084cB2.5
  • 19200701 Lecture
    Algebra and Theory of Numbers (Alexander Schmitt)
    Schedule: Mo 08:00-10:00, Mi 08:00-10:00 (Class starts on: 2025-10-15)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Comments

    Subject matter:
    Selected topics from:

        Divisibility into rings (especially Z- and polynomial rings); residual classes and congruencies; modules and ideals
        Euclidean, principal ideal and factorial rings
        The quadratic law of reciprocity
        Primality tests and cryptography
        The structure of abel groups (or modules about main ideal rings)
        Symmetric function set
        Body extensions, Galois correspondence; constructions with compasses and rulers
        Non-Label groups (set of Lagrange, normal dividers, dissolvability, sylow groups)

  • 19200702 Practice seminar
    Practice seminar for Algebra and Theory of Numbers (Alexander Schmitt)
    Schedule: Mi 14:00-16:00, Do 14:00-16:00 (Class starts on: 2025-10-15)
    Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
    

• Discrete Mathematics I

  0084cB3.2
  • 19202001 Lecture
    Discrete Geometrie I (Christian Haase)
    Schedule: Di 10:00-12:00, Mi 12:00-14:00 (Class starts on: 2025-10-14)
    Location: A3/SR 120 (Arnimallee 3-5)
    

    Additional information / Pre-requisites

    Solid background in linear algebra. Knowledge in combinatorics and geometry is advantageous.

    Comments

    Physical presence in the exercises on Wednesdays is mandatory.

    This is the first in a series of three courses on discrete geometry. The aim of the course is a skillful handling of discrete geometric structures including analysis and proof techniques. The material will be a selection of the following topics:
    Basic structures in discrete geometry

    • polyhedra and polyhedral complexes
    • configurations of points, hyperplanes, subspaces
    • Subdivisions and triangulations (including Delaunay and Voronoi)
    • Polytope theory
    • Representations and the theorem of Minkowski-Weyl
    • polarity, simple/simplicial polytopes, shellability
    • shellability, face lattices, f-vectors, Euler- and Dehn-Sommerville
    • graphs, diameters, Hirsch (ex-)conjecture
    • Geometry of linear programming
    • linear programs, simplex algorithm, LP-duality
    • Combinatorial geometry / Geometric combinatorics
    • Arrangements of points and lines, Sylvester-Gallai, Erdos-Szekeres
    • Arrangements, zonotopes, zonotopal tilings, oriented matroids
    • Examples, examples, examples
    • regular polytopes, centrally symmetric polytopes
    • extremal polytopes, cyclic/neighborly polytopes, stacked polytopes
    • combinatorial optimization and 0/1-polytopes

     

    For students with an interest in discrete mathematics and geometry, this is the starting point to specialize in discrete geometry. The topics addressed in the course supplement and deepen the understanding for discrete-geometric structures appearing in differential geometry, topology, combinatorics, and algebraic geometry.

     

     

     

     

     

     

     

     

     

    Suggested reading

    • G.M. Ziegler "Lectures in Polytopes"
    • J. Matousek "Lectures on Discrete Geometry"
    • Further literature will be announced in class.

  • 19202002 Practice seminar
    Practice seminar for Discrete Geometrie I (Sofia Garzón Mora, Christian Haase)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-10-15)
    Location: A6/SR 031 Seminarraum (Arnimallee 6)
    

• Numerical Mathematics II

  0084cB3.4
  • 19202101 Lecture
    Basic Module: Numeric II (Robert Gruhlke)
    Schedule: Mo 12:00-14:00, Mi 12:00-14:00 (Class starts on: 2025-10-15)
    Location: A3/Hs 001 Hörsaal (Arnimallee 3-5)
    

    Comments

    Description: Extending basic knowledge on odes from Numerik I, we first concentrate on one-step methods for stiff and differential-algebraic systems and then discuss Hamiltonian systems. In the second part of the lecture we consider the iterative solution of large linear systems.

    Target Audience: Students of Bachelor and Master courses in Mathematics and of BMS

    Prerequisites: Basics of calculus (Analysis I, II) linear algebra (Lineare Algebra I, II) and numerical analysis (Numerik I)

  • 19202102 Practice seminar
    Practice seminar for Basic Module: Numeric II (André-Alexander Zepernick)
    Schedule: Mi 10:00-12:00, Fr 08:00-10:00 (Class starts on: 2025-10-15)
    Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
    

• Modules w/o courses in this semester

  179 Modules
  • Operating Systems 0089bA1.1
  • Mobile Communications 0089bA1.10
  • Network-Based Information Systems 0089bA1.12
  • Robotics 0089bA1.14
  • Semantic Business Process Management 0089bA1.15
  • Semantics of Programming Languages 0089bA1.16
  • Seminar: Data Management 0089bA1.18
  • Seminar: Artificial Intelligence 0089bA1.19
  • Image Processing 0089bA1.2
  • Seminar: Programming Languages 0089bA1.20
  • Software Project: Data Management 0089bA1.21
  • Software Project: Mobile Communications 0089bA1.22
  • Software Project: Compiler Construction 0089bA1.23
  • Telematics 0089bA1.27
  • Transactional Systems 0089bA1.28
  • Compiler Construction 0089bA1.29
  • Computer Graphics 0089bA1.3
  • Distributed Systems 0089bA1.30
  • XML Technology 0089bA1.31
  • Telematics Project 0089bA1.32
  • Seminar: Database Systems 0089bA1.33
  • Seminar: Modern Web Technology 0089bA1.34
  • Software Technology Project 0089bA1.35
  • Module (lecture/integrated exercise 2 hrs/wk) 1 0089bA1.37
  • Module (course 2 hrs/wk) 2 0089bA1.38
  • Module (project 1 hr/wk) 3 0089bA1.39
  • Computer Vision 0089bA1.4
  • Module (lecture+exercise 2+1 hrs/wk) 4 0089bA1.40
  • Module (seminar 2 hrs/wk) 5 0089bA1.41
  • Module (lecture+exercise 2+2 hrs/wk) 6 0089bA1.42
  • Module (seminar+practical 1+1 hrs/wk) 7 0089bA1.43
  • Module (project seminar 3 hrs/wk) 8 0089bA1.44
  • Module (lecture+exercise 4+2 hrs/wk) 9 0089bA1.45
  • Module (lecture+exercise 2+2 hrs/wk) 10 0089bA1.46
  • Module (practical 4 hrs/wk) 11 0089bA1.47
  • Module (project 4 hrs/wk) 12 0089bA1.48
  • Seminar: IT Security 0089bA1.49
  • Database Technology 0089bA1.5
  • Module (lecture+exercise 2+2 hrs/wk) 13 0089bA1.50
  • Module (lecture+exercise 2+2 hrs/wk) 14 0089bA1.51
  • Module (lecture+exercise 2+2 hrs/wk) 15 0089bA1.52
  • Module (project 4 hrs/wk) 16 0089bA1.53
  • Module (4 lecture + 2 exercise hrs/wk, 8 CP) No. 17 0089bA1.54
  • Module (4 lecture + 2 exercise hrs/wk, 8 CP) No. 18 0089bA1.55
  • Module (project 4 hrs/wk) No. 19 0089bA1.56
  • Module (project 4 hrs/wk) No. 20 0089bA1.57
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 21 0089bA1.58
  • Module (practical 2 hrs/wk (contact hours), 4 CP) No. 22 0089bA1.59
  • Empirical Evaluation in Computer Science 0089bA1.6
  • Module (practical 2 hrs/wk, 4 CP) No. 23 0089bA1.60
  • Advanced Aspects of Functional Programming 0089bA1.7
  • Computer Security 0089bA1.8
  • Artificial Intelligence 0089bA1.9
  • Model-driven Software Development 0089cA1.11
  • Computer Security 0089cA1.16
  • Compiler Construction 0089cA1.19
  • Computer Graphics 0089cA1.2
  • Practices in Professional Software Development 0089cA1.22
  • Selected Topics in Applied Computer Science 0089cA1.31
  • Fundamentals of Software Testing 0089cA1.7
  • Current Research Topics in Algorithmics 0089bA2.1
  • Software Project: Application of Algorithms 0089bA2.11
  • Module (lecture/integrated exercise 2 hrs/wk) 1 0089bA2.12
  • Module (course 2 hrs/wk) 2 0089bA2.13
  • Module (lecture+exercise 2+1 hrs/wk) 3 0089bA2.14
  • Module (Seminar 2 hrs/wk) 4 0089bA2.15
  • Module (lecture+exercise 2+2 hrs/wk) 5 0089bA2.16
  • Module (lecture+exercise 4+2 hrs/wk) 6 0089bA2.17
  • Module (lecture+exercise 2+2 hrs/wk) 7 0089bA2.18
  • Module (practical 4 hrs/wk) 8 0089bA2.19
  • Computational Geometry 0089bA2.2
  • Module (project 4 hrs/wk) 9 0089bA2.20
  • Module (seminar 2 hrs/wk) No. 10 0089bA2.21
  • Module (2 lecture + 2 exercise hrs/wk, 5 CP) No. 11 0089bA2.22
  • Module (4 lecture + 2 exercise hrs/wk, 8 CP) No. 12 0089bA2.23
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 13 0089bA2.24
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 14 0089bA2.25
  • Selected Topics in Algorithims 0089bA2.3
  • Advanced Algorithms 0089bA2.4
  • Cryptography and Security in Distributed Systems 0089bA2.6
  • Model Checking 0089bA2.7
  • Seminar: Algorithms 0089bA2.8
  • Model Checking 0089cA2.2
  • Computational Geometry 0089cA2.4
  • Selected Topics in Theoretical Computer Science 0089cA2.5
  • Advanced topics in Theoretical Computer Science 0089cA2.6
  • Module (lecture/integrated exercise 2 hrs/wk) 1 0089bA3.10
  • Module (course 2 hrs/wk) 2 0089bA3.11
  • Module (project 1 hr/wk) 3 0089bA3.12
  • Module (lecture+exercise 2+1 hrs/wk) 4 0089bA3.13
  • Module (seminar 2 hrs/wk) 5 0089bA3.14
  • Module (lecture+exercise 2+2 hrs/wk) 6 0089bA3.15
  • Module (seminar+practical 1+1 hrs/wk 7 0089bA3.16
  • Module (project seminar 3 hrs/wk) 8 0089bA3.17
  • Module (lecture+exercise 4+2 hrs/wk) 9 0089bA3.18
  • Module (lecture+exercise 2+2 hrs/wk) 10 0089bA3.19
  • Microprocessor Lab 0089bA3.2
  • Module (practical 4 hrs/wk) 11 0089bA3.20
  • Module (project 4 hrs/wk) 12 0089bA3.21
  • Module (lecture+exercise 2+2 hrs/wk) 13 0089bA3.22
  • Module (lecture+exercise 2+2 hrs/wk) 14 0089bA3.23
  • Module (project 4 hrs/wk) 15 0089bA3.24
  • Module (seminar 2 hrs/wk) No. 16 0089bA3.25
  • Module (2 lecture + 4 exercise hrs/wk, 8 CP) No. 17 0089bA3.26
  • Module (2 lecture + 4 exercise hrs/wk, 8 CP) No. 18 0089bA3.27
  • Module (2 lecture + 4 exercise hrs/wk, 10 CP) No. 19 0089bA3.28
  • Seminar: Computer Systems 0089bA3.6
  • Selected Topics in Technical Computer Science 0089cA3.12
  • Mobile Communications 0089cA3.3
  • Project Management 0089bA4.25
  • Module (project 1 hr/wk) 1 0089bA4.26
  • Starting a Business in IT 0089bA4.27
  • Module (lecture/integrated exercise 2 hrs/wk) 2 0089bA4.28
  • Module (course 2 hrs/wk) 3 0089bA4.29
  • Module (project 1 hr/wk) 4 0089bA4.30
  • Module (lecture+exercise 2+1 hrs/wk) 5 0089bA4.31
  • Module (seminar 2 hrs/wk) 6 0089bA4.32
  • Module (lecture+exercise 2+2 hrs/wk) 7 0089bA4.33
  • Module (seminar+practical 1+1 hrs/wk) 8 0089bA4.34
  • Module (project seminar 3 hrs/wk) 9 0089bA4.35
  • Module (lecture+exercise 4+2 hrs/wk) 10 0089bA4.36
  • Module (lecture+exercise 2+2 hrs/wk) 11 0089bA4.37
  • Module (practical 4 hrs/wk) 12 0089bA4.38
  • Module (project 4 hrs/wk) 13 0089bA4.39
  • Module (lecture+exercise 2+2 hrs/wk) 14 0089bA4.42
  • Module (lecture+exercise 2+2 hrs/wk) 15 0089bA4.43
  • Module (lecture+exercise 2+2 hrs/wk) 16 0089bA4.44
  • Module (project 4 hrs/wk) 17 0089bA4.45
  • Module (seminar 2 hrs/wk) No. 18 0089bA4.46
  • Module (seminar 2 hrs/wk) No. 19 0089bA4.47
  • Module (2 lecture + 4 exercise hrs/wk, 8 CP) No. 20 0089bA4.48
  • Module (2 lecture + 4 exercise hrs/wk, 8 CP) No. 21 0089bA4.49
  • Digital Video 0089bA4.5
  • Module (2 lecture + 2 practical hrs/wk, 5 CP) No. 22 0089bA4.50
  • Module (2 lecture + 2 practical hrs/wk, 5 CP) No. 23 0089bA4.51
  • Module (practical 2 hrs/wk, 4 CP) No. 24 0089bA4.52
  • Module (practical 2 hrs/wk, 4 CP) No. 25 0089bA4.53
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 26 0089bA4.54
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 27 0089bA4.55
  • E-Learning Platforms 0089bA4.6
  • Module (project 1 hr/wk) 1 0089bA4.7
  • Medical Image Processing 0089bA4.9
  • Special Lecture: Graph Theory 0084bC3.3
  • Special Lecture: Cryptography 0084bC3.6
  • Main Lecture: Logic and Model Theory 0084bC4.1
  • Probability and Statistics I 0084cA1.8
  • Advanced Module: Combinatorics and Graph Theory 0280aA2.1
  • Specialization Module: Discrete Geometry and Optimization 0280aA2.2
  • Special Module: Visualization 0280aA4.6
  • Algorithmische Bioinformatik 0260aA1.4
  • Statistics I for Students of Life Sciences 0260aA2.5
  • Statistics II for Students of Life Sciences 0260aA2.6
  • Diskrete Mathematik 0262aA1.1
  • Algorithmen in der Systembiologie 0262aA1.3
  • Fortgeschrittene Algorithmen in der Bioinformatik 0262aA1.4
  • Sequenzanalyse und molekulare Evolution (A) 0262aA2.1
  • Vertiefung statistischer Methoden in Genetik und Bioinformatik (B) 0262aA2.10
  • Sequenzanalyse und molekulare Evolution (B) 0262aA2.2
  • Mathematische Aspekte und Algorithmen der Strukturbiologie (A) 0262aA2.3
  • Mathematische Aspekte und Algorithmen der Strukturbiologie (B) 0262aA2.4
  • Simulating Molecular and Cellular Processes (A) 0262aA2.5
  • Simulating Molecular and Cellular Processes (B) 0262aA2.6
  • Advanced Statistical Methods in Genetics and Bioinformatics (A) 0262aA2.9
  • Theoretical Physics 1 0182aA2.1
  • Theoretical Physics 2 0182aA2.2
  • Atomic and Molecular Physics 0182aA4.2
  • Solid State Physics 0182aA4.3
  • Biophysics 0182aA4.4
  • Introduction to Astronomy and Astrophysics 0182aA4.5
  • Advanced Module: Epistemology and Philosophy of Science 0044cB1.1
  • Advanced Module: Philosophy of Language and Hermeneutics 0044cB1.2
  • Advanced Module: Metaphysics and Ontology 0044cB1.3
  • Advanced Module: Ethics 0044cB1.4
  • Advanced Module: Political/Social Philosophy and Anthropology 0044cB1.5
  • Advanced Module: Aesthetics 0044cB1.6
  • Cognitive and Experimental Psychology 0281bA1.1
  • Differential and Personality Psychology 0281bA1.3
  • Social Psychology 0281bA1.4
  • Developmental Psychology 0281bA1.5