Computer Science

• Project Seminar: Data Management Systems

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  • 19303811 Seminar
    Project Seminar: Data Management (Muhammed-Ugur Karagülle, Agnès Voisard)
    Schedule: Do 12:00-14:00 (Class starts on: 2024-10-17)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Requirement

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

    Comments

    Content

    A project seminar serves as preparation of a thesis (bachelor or master) in the AGDB. The focus of this project seminar lies on the analysis and visualization of medical data. Additionally, we will realize a small software project.

    Suggested reading

    Wird bekannt gegeben.

• Seminar: Contributions to Software Engineering

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  • 19305811 Seminar
    Seminar: Contributions to Software Engineering (Lutz Prechelt)
    Schedule: Do 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-09-02)
    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

• Seminar: Data Management

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  • 19306017 Seminar / Undergraduate Course
    Seminar/Proseminar: Data Visualization and Mining (Agnès Voisard)
    Schedule: Do 10:00-12:00 (Class starts on: 2024-10-17)
    Location: A6/SR 009 Seminarraum (Arnimallee 6)
    

    Additional information / Pre-requisites

    Preliminary discussion date to be announced.

    Comments

    Advanced module data visualization and data mining.

    Suggested reading

    Wird bekannt gegeben.

• Software Project: Data Management

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  • 19308412 Project Seminar
    Software Project: Data Management (Agnès Voisard, Muhammed-Ugur Karagülle)
    Schedule: Mo 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    Students in the Master's or Bachelor's programme

     

    Prerequisites

    Good programming skills, introduction to database systems.

    Comments

    Subject of the project: either development of software together with a company (in this case: 4­ weeks fulltime August/September) or we build a so called NoSQL system. Decision in March. Further information are published in the KVV.

    Suggested reading

    Wird bekannt gegeben. / To be announced.

• Software Project: Web Technologies

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  • 19314012 Project Seminar
    Software Project: Semantic Technologies (Adrian Paschke)
    Schedule: Mi 14:00-16:00 (Class starts on: 2024-10-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Additional information / Pre-requisites

    Further information can be found on the course website of the AG Corporate Semantic Web.

    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 AI 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 AI 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.

  • 19319312 Project Seminar
    Implementation Project: Coding IxD (Claudia Müller-Birn)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/winter_term_2022_23/software_project_coding_ixd.html   Address

    Sophienstrasse 22a, 2.HH, 2.Stock, 10178 Berlin

    www.interdisciplinary-laboratory.hu-berlin.de

     

    Comments

    Coding IxD: Designing Neoanalog Artefacts

    In this course, we co-educate computer scientists and product designers. Beyond experiencing interdisciplinary work, we want students to envision interactive systems that are intelligent: by this, we mean an intelligence through code that is carefully using material, form, and context, while profoundly respecting both human capabilities and vulnerabilities.

    We understand this course as experimental space, where different perspectives meet, exchange, and evolve. Each semester, based on small project teams of up to five members, students are challenged to examine a specific application context. Within this context, the teams envision a new application or product concept.

    We guide this process through various carefully tuned methods that are used to spark their ideas. Students iterate through several rounds of ideation and refine their concept in different prototype versions. The most compelling or promising interaction concept, the one that allows grasping the quality and essence of the product concept is implemented in a working prototype.

    Students are accompanied by a team of experienced designers and computer scientists but also by guest experts that provide feedback to the various design iterations. If needed, special workshops are organized to cover specific topics ranging from prototyping to project management. The whole course is evaluated continuously to enhance our methodological toolbox.

    This course offering is a cooperation of the r Human-Centered Computing Research Group at the Institute of Computer Science at the Freie Universität Berlin and the Product Design Department at the Weißensee Kunsthochschule Berlin (KHB).

    Besides the regular weekly meetings, the KHB provides complimentary workshops each Monday from 10 AM to 1 PM where participation for computer science students is optional.

    Suggested reading

    Zimmerman, John, Jodi Forlizzi, and Shelley Evenson. "Research through design as a method for interaction design research in HCI." Proceedings of the SIGCHI conference on Human factors in computing systems. 2007.

    Pierce, James, et al. "Expanding and refining design and criticality in HCI." Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. 2015.

    Anthony Dunne and Fiona Raby. 2013. Speculative Everything: Design, Fiction, and Social Dreaming. The MIT Press.

• Advanced Topics in Data Management

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  • 19304801 Lecture
    Geospatial Databases (Agnès Voisard)
    Schedule: Di 14:00-16:00 (Class starts on: 2024-10-15)
    Location: T9/055 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: 2024-10-17)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

• Seminar: Database Systems

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  • 19306017 Seminar / Undergraduate Course
    Seminar/Proseminar: Data Visualization and Mining (Agnès Voisard)
    Schedule: Do 10:00-12:00 (Class starts on: 2024-10-17)
    Location: A6/SR 009 Seminarraum (Arnimallee 6)
    

    Additional information / Pre-requisites

    Preliminary discussion date to be announced.

    Comments

    Advanced module data visualization and data mining.

    Suggested reading

    Wird bekannt gegeben.

• Software Technology Project

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  • 19323612 Project Seminar
    The AMOS Project (Lutz Prechelt, Dirk Riehle)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Educational objectives and competencies

    • Students learn about software products and software development in an industry context
    • Students learn about agile methods, in particular Scrum and Extreme Programming
    • Students learn about open source software development and its underlying principles
    • Students gain practical hands-on experience with a Scrum process and XP technical practices

    Target group

    Students of computer science (and related fields). If you want to play the software developer role, you should have had practical programming experience. This is not a course to learn programming.

    Language

    English (lectures in English, team meeting German or English by choice of student team)

    Other

    • SWS: 4 SWS (2 SWS lecture, 2 SWS team meeting)
    • Semester: Every winter semester
    • Modality: Online, across multiple universities
    • Tags: Scrum

     

    Comments

    This course teaches agile methods (Scrum and XP) and open source tools using a single semester-long project. It takes place online and across multiple universities.

    Topics covered are:

    • Agile methods and related software development processes
    • Scrum roles, process practices, including product and engineering management
    • Technical practices like refactoring, continuous integration, and test-driven development
    • Principles and best practices of open source software development

    The project is a software development project in which each student team works with an industry partner who provides the idea for the project. This is a practical hands-on experience. Students take on the role of a software developer. In this role, they estimate and evaluate the effort of requirements and implement them in the project.

    Students will be organized into teams of 7-8 people, combining product owners with software developers. An industry partner will provide requirements to be worked out in detail by the product owners and to be realized by the software developers. The available projects will be presented in the run-up to the course.

    The course consists of 90min lectures (participation voluntary) followed by a 90min team meeting (participation mandatory).
     

    Attention: External course, separate registration is required, see https://amos.uni1.de

    Suggested reading

    http://goo.gl/5Wqnr7

• Software Project: Artificial Intelligence

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  • 19314012 Project Seminar
    Software Project: Semantic Technologies (Adrian Paschke)
    Schedule: Mi 14:00-16:00 (Class starts on: 2024-10-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Additional information / Pre-requisites

    Further information can be found on the course website of the AG Corporate Semantic Web.

    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 AI 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 AI 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.

• Computer Vision

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  • 19315501 Lecture
    Computer Vision (Tim Landgraf)
    Schedule: Mi 10:00-12:00 (Class starts on: 2024-10-16)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    

    Comments

    Contents:

    The most frequent tasks in Computer Vision are object (or event) detection and object tracking. In contrast to the field of image processing we often work on a sequence of images (a.k.a. video). In the lecture we will review a number of essential landmark publications and learn about cutting edge technologies of today.

  • 19315502 Practice seminar
    Practice seminar for Computer Vision (Tim Landgraf)
    Schedule: Di 14:00-16:00 (Class starts on: 2024-10-15)
    Location: T9/049 Seminarraum (Takustr. 9)
    

• Seminar: IT Security

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  • 19320811 Seminar
    Selected Subjects of IT Security & Privacy (Marian Margraf)
    Schedule: Mo 14:00-16:00 (Class starts on: 2024-10-14)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    

    Comments

    The seminar covers topics related to IT security and privacy. In particular, we deal with selected topics:

    • Usable security and privacy
    • Mobile security
    • Cache-based sidechannel attacks

    One topic is worked on by one person and presented to the other participants in a presentation. At the end of the semester, a seminar paper on the respective topic must also be submitted. Details will be discussed at the first event.
    The seminar is offered in German and, if necessary, in English.

    Suggested reading

    Daniel J. Bernstein, Johannes Buchmann, Erik Dahmen (Eds.): Post-Quantum Cryptography.

• Practices in Professional Software Development

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  • 19311824 Methodenkurs
    Practices of Professional Software Development (Lutz Prechelt)
    Schedule: Mo 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Main source for the concepts dealt with is the website http://clean-code-developer.de

    Course website: http://www.mi.fu-berlin.de/w/SE/KursProfessionelleSWEntwicklung2024

    Comments

    When studying Computer Science at university you mainly focus on concepts. This approach generally makes sense as these conceps are far more persistent and applicable in a broader sense than concrete details would be. Many details, however, which are important for concrete software development, are falling by the wayside. The course is supposed to reduce this deficit.

    In it we mainly focus on concepts too, but always only on those which directly have to do with software development, and make sure to apply them precisely, personally in practice -- reflecting its use jointly (something which distinguisdes this course from most other software projects).

    The concepts dealt with and practiced may be assigned to three different but closeky connected spheres:

    • software development and structuring (object-oriented) Softwareentwurf und -strukturierung (und zwar objektorientiert)
    • approaches (for example in the areas prototyping, automatisation, incremental improvement)
    • personality development (aspects like consistency, responsibility, communicational skills)

     

    Important: Each participant needs to have a software project of his/her own, which has been started far in advance or the course (within a company, for founding a company or as an open source project), on which he/she works on a weekly basis for the entire duration of the course (mainly in a team) and which serves as training ground for the concepts.

    This is a hard prerequisite for participation.

  • 19311813 Lab Seminar
    Professional Software Development Lab (Lutz Prechelt)
    Schedule: Mo 14:00-16:00 (Class starts on: 2024-10-14)
    Location: T9/055 Seminarraum (Takustr. 9)
    

• Current research topics in Applied Computer Science

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  • 19320701 Lecture
    Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 10:00-12:00 (Class starts on: 2024-10-18)
    Location: T9/055 Seminarraum (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, 2020.
    • Weitere Literaturhinweise werden zu den einzelnen Themenblöcken bereitgestellt.

  • 19327201 Lecture
    Data compression (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2024-10-14)
    Location: T9/049 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 Cancelled
    Data Visualization (Claudia Müller-Birn)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/winter_term_2021_22/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

    Textbuch

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

     

    Zusätzliche Literatur

    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
    Cryptocurrencies and Blockchain (Katinka Wolter, Justus Purat)
    Schedule: Di 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    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

  • 19333001 Lecture
    Cybersecurity and AI I: Privacy, Biometry, Certification (Gerhard Wunder)
    Schedule: Di 12:00-14:00 (Class starts on: 2024-10-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    
  • 19336801 Lecture
    Integrative analysis and including prior knowledge for data in the life sciences (Katharina Baum, Pauline Hiort, Pascal Iversen)
    Schedule: Mi 10:00-12:00 (Class starts on: 2024-10-16)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

    Comments

    Especially in the life sciences, data of different origins are often available for a question, and researchers already have prior knowledge, for example on dynamic aspects, or on spatial or regulatory relationships between entities. This course deals with analysis methods that can combine different data and prior knowledge. For example, we discuss how to link continuous and categorical data in mixed models, but also network integration, or multi-factorial matrix multiplication. A focus topic will deal with various approaches to informed machine learning such as graph-neural networks, transfer learning or current research methods such as simulation-based pre-training. The focus here is explicitly not on the processing of images, but on tabular or other data types. This course will be offered in English.

  • 19320702 Practice seminar
    Practice seminar for Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 12:00-14:00 (Class starts on: 2024-10-18)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    
  • 19327202 Practice seminar
    Practice seminar for Data Compression (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/049 Seminarraum (Takustr. 9)
    
  • 19328302 Practice seminar Cancelled
    Data Visualization (Claudia Müller-Birn)
    Schedule: -
    Location: keine Angabe
    
  • 19328602 Practice seminar
    Practice Session on Cryptocurrencies (Justus Purat)
    Schedule: Do 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-09-27)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19333002 Practice seminar
    Practice seminar for Cybersecurity and AI I (Gerhard Wunder)
    Schedule: Mo 14:00-16:00 (Class starts on: 2024-10-14)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    
  • 19336802 Practice seminar
    Integrative analysis of biomedical data tutorials (Katharina Baum)
    Schedule: Fr 10:00-12:00 (Class starts on: 2024-10-18)
    Location: T9/046 Seminarraum (Takustr. 9)
    

• Special Aspects of Applied Computer Science

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  • 19320701 Lecture
    Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 10:00-12:00 (Class starts on: 2024-10-18)
    Location: T9/055 Seminarraum (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, 2020.
    • Weitere Literaturhinweise werden zu den einzelnen Themenblöcken bereitgestellt.

  • 19327201 Lecture
    Data compression (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2024-10-14)
    Location: T9/049 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 Cancelled
    Data Visualization (Claudia Müller-Birn)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/winter_term_2021_22/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

    Textbuch

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

     

    Zusätzliche Literatur

    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
    Cryptocurrencies and Blockchain (Katinka Wolter, Justus Purat)
    Schedule: Di 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    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

  • 19333001 Lecture
    Cybersecurity and AI I: Privacy, Biometry, Certification (Gerhard Wunder)
    Schedule: Di 12:00-14:00 (Class starts on: 2024-10-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    
  • 19336801 Lecture
    Integrative analysis and including prior knowledge for data in the life sciences (Katharina Baum, Pauline Hiort, Pascal Iversen)
    Schedule: Mi 10:00-12:00 (Class starts on: 2024-10-16)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

    Comments

    Especially in the life sciences, data of different origins are often available for a question, and researchers already have prior knowledge, for example on dynamic aspects, or on spatial or regulatory relationships between entities. This course deals with analysis methods that can combine different data and prior knowledge. For example, we discuss how to link continuous and categorical data in mixed models, but also network integration, or multi-factorial matrix multiplication. A focus topic will deal with various approaches to informed machine learning such as graph-neural networks, transfer learning or current research methods such as simulation-based pre-training. The focus here is explicitly not on the processing of images, but on tabular or other data types. This course will be offered in English.

  • 19320702 Practice seminar
    Practice seminar for Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 12:00-14:00 (Class starts on: 2024-10-18)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    
  • 19327202 Practice seminar
    Practice seminar for Data Compression (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/049 Seminarraum (Takustr. 9)
    
  • 19328302 Practice seminar Cancelled
    Data Visualization (Claudia Müller-Birn)
    Schedule: -
    Location: keine Angabe
    
  • 19328602 Practice seminar
    Practice Session on Cryptocurrencies (Justus Purat)
    Schedule: Do 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-09-27)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19333002 Practice seminar
    Practice seminar for Cybersecurity and AI I (Gerhard Wunder)
    Schedule: Mo 14:00-16:00 (Class starts on: 2024-10-14)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    
  • 19336802 Practice seminar
    Integrative analysis of biomedical data tutorials (Katharina Baum)
    Schedule: Fr 10:00-12:00 (Class starts on: 2024-10-18)
    Location: T9/046 Seminarraum (Takustr. 9)
    

• Special Aspects of Software Development

  0089cA1.30
  • 19320701 Lecture
    Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 10:00-12:00 (Class starts on: 2024-10-18)
    Location: T9/055 Seminarraum (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, 2020.
    • Weitere Literaturhinweise werden zu den einzelnen Themenblöcken bereitgestellt.

  • 19320702 Practice seminar
    Practice seminar for Secure Software Engineering (Jörn Eichler)
    Schedule: Fr 12:00-14:00 (Class starts on: 2024-10-18)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    

• Selected Topics in Applied Computer Science

  0089cA1.31
  • 19330101 Lecture
    Machine Learning for Data Science (Grégoire Montavon)
    Schedule: Di 16:00-18:00, Do 16:00-18:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-15)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Comments

    Qualifikationsziele:

    The course provides an overview of machine learning methods and algorithms for different learning tasks, namely supervised, unsupervised and reinforcement learning.

    In the first part of the course, for each task the main algorithms and techniques will be covered including experimentation and evaluation aspects.

    In the second part of the course, we will focus on specific learning challenges including high-dimensionality, non-stationarity, label-scarcity and class-imbalance.

    By the end of the course, you will have learned how to build machine learning models for different problems, how to properly evaluate their performance and how to tackle specific learning challenges.

    Inhalte

     Es werden Themen aus folgenden Gebieten behandelt:

     

    • Experiment Design
    • Sampling Techniques
    • Data cleansing
    • Storage of large data sets
    • Data visualization and graphs
    • Probabilistic data analysis
    • Prediction methods
    • Knowledge discovery
    • Neural networks
    • Support vector machines
    • Reinforcement learning and agent models

  • 19330102 Practice seminar
    Practice Seminar Machine Learning DatSci (Grégoire Montavon)
    Schedule: Mi 16:00-18:00 (Class starts on: 2024-10-16)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

• Current Research Topics in Algorithmics

  0089bA2.1
  • 19320501 Lecture
    Quantum Cryptanalysis (Marian Margraf)
    Schedule: Di 10:00-12:00, Do 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    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.

  • 19320502 Practice seminar
    Practice seminar for Cryptanalysis (Marian Margraf)
    Schedule: -
    Location: keine Angabe
    

• Module (lecture+exercise 2+2 hrs/wk) 5

  0089bA2.16
  • 19320501 Lecture
    Quantum Cryptanalysis (Marian Margraf)
    Schedule: Di 10:00-12:00, Do 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    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.

  • 19320502 Practice seminar
    Practice seminar for Cryptanalysis (Marian Margraf)
    Schedule: -
    Location: keine Angabe
    

• Advanced Algorithms

  0089cA2.1
  • 19303501 Lecture
    Advanced Algorithms (László Kozma)
    Schedule: Di 10:00-12:00, Fr 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    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

    This course will focus on the design and analysis of algorithms, with topics including:

    • general principles of algorithm design,
    • randomized algorithms,
    • dynamic programming,
    • flow problems on graphs,
    • amortized analysis and advanced data structures,
    • theory of NP-completeness,
    • approximation methods for hard problems,
    • other topics.

    Prerequisites are basic knowledge of algorithms and relevant mathematics. All Bachelor and Master students interested in advanced algorithmic techniques are welcome. Lectures are in English.

    Suggested reading

    • Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms, 4th Ed. MIT Press 2022
    • Kleinberg, Tardos: Algorithm Design, Addison-Wesley 2005.
    • Sedgewick, Wayne: Algorithms, 4th Ed., Addison-Wesley 2016

  • 19303502 Practice seminar
    Practice seminar for Advanced Algorithms (László Kozma)
    Schedule: Fr 08:00-10:00, Fr 14:00-16:00 (Class starts on: 2024-10-18)
    Location: T9/046 Seminarraum (Takustr. 9)
    

• Current Research Topics in Theoretical Computer Science

  0089cA2.3
  • 19320501 Lecture
    Quantum Cryptanalysis (Marian Margraf)
    Schedule: Di 10:00-12:00, Do 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    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.

  • 19320502 Practice seminar
    Practice seminar for Cryptanalysis (Marian Margraf)
    Schedule: -
    Location: keine Angabe
    

• Selected Topics in Theoretical Computer Science

  0089cA2.5
  • 19315401 Lecture
    Graph and Network Algorithms (Günther Rothe)
    Schedule: Mo 14:00-16:00, Fr 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target Audience

    Masters students in Computer Science or Mathematics, advanced Bachelor students.

    Prerequisites

    "Advanced Algorithms" or a similar class

    Comments

    Graphs and networks are an important modeling tool for all kinds of relations in Computer Science and beyond, for example social networks, traffic networks, and so on. We will treat algorithmic problems that arise in this context:

    • analysis of networks
    • optimization in graphs
    • graph drawing

    Suggested reading

    Wird noch bekannt gegeben.

  • 19315402 Practice seminar
    Practice seminar for Graph and Network Algorithms (Mahmoud Elashmawi, Günther Rothe)
    Schedule: Mi 12:00-14:00 (Class starts on: 2024-10-16)
    Location: T9/053 Seminarraum (Takustr. 9)
    

• Advanced topics in Theoretical Computer Science

  0089cA2.6
  • 19315401 Lecture
    Graph and Network Algorithms (Günther Rothe)
    Schedule: Mo 14:00-16:00, Fr 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target Audience

    Masters students in Computer Science or Mathematics, advanced Bachelor students.

    Prerequisites

    "Advanced Algorithms" or a similar class

    Comments

    Graphs and networks are an important modeling tool for all kinds of relations in Computer Science and beyond, for example social networks, traffic networks, and so on. We will treat algorithmic problems that arise in this context:

    • analysis of networks
    • optimization in graphs
    • graph drawing

    Suggested reading

    Wird noch bekannt gegeben.

  • 19315402 Practice seminar
    Practice seminar for Graph and Network Algorithms (Mahmoud Elashmawi, Günther Rothe)
    Schedule: Mi 12:00-14:00 (Class starts on: 2024-10-16)
    Location: T9/053 Seminarraum (Takustr. 9)
    

• Special aspects of Theoretical Computer Science

  0089cA2.7
  • 19320501 Lecture
    Quantum Cryptanalysis (Marian Margraf)
    Schedule: Di 10:00-12:00, Do 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    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: 2024-10-14)
    Location: T9/049 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.

  • 19320502 Practice seminar
    Practice seminar for Cryptanalysis (Marian Margraf)
    Schedule: -
    Location: keine Angabe
    
  • 19327202 Practice seminar
    Practice seminar for Data Compression (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/049 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 12:00-14:00 (Class starts on: 2024-10-16)
    Location: T9/SR 005 Übungsraum (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
    Practice seminar for Cryptography and Security in Distributed Systems (Volker Roth)
    Schedule: Do 14:00-16:00 (Class starts on: 2024-10-17)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

• Module (seminar 2 hrs/wk) 5

  0089bA3.14
  • 19310817 Seminar / Undergraduate Course
    Seminar/Proseminar: Internet of Things & Security (Computer Systems & Telematics) (Emmanuel Baccelli)
    Schedule: Do 10:00-12:00 (Class starts on: 2024-10-17)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Comments

    Seminar Technische Informatik on Internet of Things & Security

    In large part, the Internet of Things (IoT) will consist of interconnecting low-end devices with very small memory capacity (a few kBytes) and limited energy consumption (1000 times less than a RaspberryPi).
    The IoT promises a new world of applications, but also brings up specific challenges in terms of programmability, energy efficiency, networking and security.
    After an introductory session at the start of the term, MSc students will pick a topic related to current technologies in the field of Internet of Things & Security, and write a report (IEEE LaTex template, 12 A4 pages including figures and references, single column, 1.5 spacing, 11-point font) discussing corresponding questions. At the end of the term, the participants present their results in the form a short talk (20 minutes + 10 minutes Q&A) in a meeting, which will also include cross-reviewing of student's reports. During the term, there will be deadlines for status reports, but no weekly meetings of the complete seminar group.

    Tentative Schedule: 

    Mid April: introductory session
    After 1 week: topic selection
    After 4 weeks: deadline to submit tentative outline for the report
    After 8 weeks: deadline to submit alpha version of the report
    After 10 weeks: deadline to submit beta version of the report & assignment for cross-reviewing of reports
    End of semester: - deadline to submit final version of the report    - presentation session (including Q&A and oral cross-review)

    Suggested reading

    The typical bibliography and online resources that will be in scope to survey for this seminar includes:
    - reviewing academic publications, e.g. papers from IEEE, ACM conferences/journals (available on scholar.google.com);
    - reviewing network protocol open standard specifications, e.g. IETF drafts and Request For Comments (RFC);
    - reviewing open source implementations (e.g. available on GitHub). 

     

• Seminar: Computer Systems

  0089bA3.6
  • 19310817 Seminar / Undergraduate Course
    Seminar/Proseminar: Internet of Things & Security (Computer Systems & Telematics) (Emmanuel Baccelli)
    Schedule: Do 10:00-12:00 (Class starts on: 2024-10-17)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Comments

    Seminar Technische Informatik on Internet of Things & Security

    In large part, the Internet of Things (IoT) will consist of interconnecting low-end devices with very small memory capacity (a few kBytes) and limited energy consumption (1000 times less than a RaspberryPi).
    The IoT promises a new world of applications, but also brings up specific challenges in terms of programmability, energy efficiency, networking and security.
    After an introductory session at the start of the term, MSc students will pick a topic related to current technologies in the field of Internet of Things & Security, and write a report (IEEE LaTex template, 12 A4 pages including figures and references, single column, 1.5 spacing, 11-point font) discussing corresponding questions. At the end of the term, the participants present their results in the form a short talk (20 minutes + 10 minutes Q&A) in a meeting, which will also include cross-reviewing of student's reports. During the term, there will be deadlines for status reports, but no weekly meetings of the complete seminar group.

    Tentative Schedule: 

    Mid April: introductory session
    After 1 week: topic selection
    After 4 weeks: deadline to submit tentative outline for the report
    After 8 weeks: deadline to submit alpha version of the report
    After 10 weeks: deadline to submit beta version of the report & assignment for cross-reviewing of reports
    End of semester: - deadline to submit final version of the report    - presentation session (including Q&A and oral cross-review)

    Suggested reading

    The typical bibliography and online resources that will be in scope to survey for this seminar includes:
    - reviewing academic publications, e.g. papers from IEEE, ACM conferences/journals (available on scholar.google.com);
    - reviewing network protocol open standard specifications, e.g. IETF drafts and Request For Comments (RFC);
    - reviewing open source implementations (e.g. available on GitHub). 

     

• Operating Systems

  0089cA3.1
  • 19312101 Lecture
    Systems Software (Barry Linnert)
    Schedule: Mo 10:00-12:00, Do 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-14)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    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, but may be answered in English, too.

    Homepage

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

    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: Mi 10:00-12:00 (Class starts on: 2024-10-16)
    Location: T9/049 Seminarraum (Takustr. 9)
    

• Current Research Topics in Computer Systems

  0089cA3.10
  • 19328601 Lecture
    Cryptocurrencies and Blockchain (Katinka Wolter, Justus Purat)
    Schedule: Di 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    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

  • 19328602 Practice seminar
    Practice Session on Cryptocurrencies (Justus Purat)
    Schedule: Do 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-09-27)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

• Special Aspects of Computer Systems

  0089cA3.11
  • 19327201 Lecture
    Data compression (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2024-10-14)
    Location: T9/049 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
    Cryptocurrencies and Blockchain (Katinka Wolter, Justus Purat)
    Schedule: Di 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    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

  • 19327202 Practice seminar
    Practice seminar for Data Compression (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/049 Seminarraum (Takustr. 9)
    
  • 19328602 Practice seminar
    Practice Session on Cryptocurrencies (Justus Purat)
    Schedule: Do 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-09-27)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

• Telematics

  0089cA3.5
  • 19305101 Lecture
    Telematics (Jochen Schiller)
    Schedule: Mo 12:00-14:00, Mi 10:00-12:00 (Class starts on: 2024-10-14)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

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

     

    Comments

    This course addresses communication asp. The lecture addresses topics such as:

    • Basic background: protocls, 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.

    In the supplementary exercise course the students will practically apply their knowledge.

    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 (Marius Max Wawerek)
    Schedule: Mo 16:00-18:00 (Class starts on: 2024-10-14)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

• Probability and Statistics I

  0084cA1.8
  • 19200601 Lecture
    Stochastics I (Ana Djurdjevac)
    Schedule: Mo 14:00-16:00, Mi 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Zielgruppe: Studierende ab dem 3. Semester
    Voraussetzungen: Grundkenntnisse aus Analysis und Linearer Algebra

    Comments

    Inhalt:

    • Prinzipien des Zählens; Elemente der Kombinatorik
    • Modelle vom Zufall abhängiger Vorgänge: Wahrscheinlichkeitsräume, Wahrscheinlichkeitsmaße
    • Bedingte Wahrscheinlichkeiten; Unabhängigkeit; Bayes'sche Regel
    • Zufallsvariablen und ihre Verteilungen; Kenngrössen der Verteilungen: Erwartungswert und Varianz
    • Diskrete Verteilungen: Laplace-Verteilung; Binomialverteilung; geometrische Verteilung
    • Approximation der Binomialverteilung durch die Normalverteilung;
    • Approximation der Binomialverteilung durch die Poissonverteilung
    • Verteilungen mit Dichten: Gleichverteilung; Normalverteilung; Exponentialverteilung
    • Gemeinsame Verteilungen von mehreren Zufallsvariablen: diskret und mit Dichten; Unabhängigkeit von Zufallsvariablen; bedingte Verteilungen; Summen unabhängiger Zufallsvariablen und ihre Verteilungen
    • Kenngrößen gemeinsamer Verteilungen: Erwartungswert, Kovarianz und Korrelation; bedingte Erwartung
    • Grenzwertsätze: schwaches Gesetz der großen Zahl und relative Häufigkeiten; der zentrale Grenzwertsatz
    • Datenanalyse und deskriptive Statistik: Histogramme; empirische Verteilung; Kenngrößen von Stichprobenverteilungen; Beispiele irreführender deskriptiver Statistiken; lineare Regression
    • Elementare Begriffe und Techniken des Testens und Schätzens: Maximum-Likelihood-Prinzip; Konfidenzintervalle; Hypothesentests; Fehler erster und zweiter Art

    Suggested reading

    Literatur:

    • E. Behrends: Elementare Stochastik, Springer, 2013
    • H.-O. Georgii: Stochastik: Einführung in die Wahrscheinlichkeitstheorie und Statistik, De Gruyter, 2007
    • U. Krengel: Einführung in die Wahrscheinlichkeitstheorie und Statistik, Vieweg, 2005
    • D. Meintrup, S. Schäffler, Stochastik: Theorie und Anwendungen, Springer, 2005.
    • Die meisten der oben aufgeführten Bücher gibt es online über die UB.

  • 19200602 Practice seminar
    Tutorial: Stochastics I (N.N.)
    Schedule: Mo 12:00-14:00, Di 08:00-10:00 (Class starts on: 2024-10-14)
    Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
    

• Algebra and Number Theory

  0084cB2.5
  • 19200701 Lecture
    Algebra and Theory of Numbers (Kivanc Ersoy)
    Schedule: Mo 08:00-10:00, Mi 08:00-10:00 (Class starts on: 2024-10-14)
    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 (N.N.)
    Schedule: Fr 10:00-12:00 (Class starts on: 2024-10-18)
    Location: KöLu24-26/SR 006 Neuro/Mathe (Königin-Luise-Str. 24 / 26)
    

• Discrete Mathematics I

  0084cB3.2
  • 19202001 Lecture
    Discrete Geometrie I (Georg Loho)
    Schedule: Di 10:00-12:00, Mi 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-15)
    Location: A3/SR 120 (Arnimallee 3-5)
    

    Additional information / Pre-requisites

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

    Comments

    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 (Georg Loho)
    Schedule: Mo 16:00-18:00, Fr 10:00-12:00 (Class starts on: 2024-10-14)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    

• Numerical Mathematics II

  0084cB3.4
  • 19202101 Lecture
    Basic Module: Numeric II (Volker John)
    Schedule: Mo 10:00-12:00, Mo 14:00-20:00 (Class starts on: 2024-10-14)
    Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
    

    Comments

    Description: Extending basic knowledge on initial value problems with ordinary differential equations from Numerik I, the course presents methods for stiff problems and multistep methods. In the second part of the course iterative methods for solving linear systems of equations are studied.

    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: Do 12:00-14:00 (Class starts on: 2024-10-17)
    Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
    

• Modules w/o courses in this semester

  168 Modules
  • Operating Systems 0089bA1.1
  • Mobile Communications 0089bA1.10
  • Pattern Recognition 0089bA1.11
  • Network-Based Information Systems 0089bA1.12
  • Robotics 0089bA1.14
  • Semantic Business Process Management 0089bA1.15
  • Semantics of Programming Languages 0089bA1.16
  • Seminar: Artificial Intelligence 0089bA1.19
  • Image Processing 0089bA1.2
  • Seminar: Programming Languages 0089bA1.20
  • Software Project: Mobile Communications 0089bA1.22
  • Software Project: Compiler Construction 0089bA1.23
  • Software Processes 0089bA1.25
  • 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: Modern Web Technology 0089bA1.34
  • 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
  • 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
  • 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
  • Fundamentals of Software Testing 0089cA1.7
  • 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 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
  • 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 (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
  • Selected Topics in Technical Computer Science 0089cA3.12
  • Microprocessor Lab 0089cA3.2
  • 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
  • Numerical Mathematics I 0084cA1.9
  • 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