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Bachelor's prog...  
Course

Computer Science

Bachelor's programme in Computer Science (150 cp, 2007 study regulations)

0086b_k137
  • Non-Sequential Programming

    0086bA1.4
    • 19322101 Lecture
      Concurrent, Parallel, and Distributed Programming (Barry Linnert, Claudia Müller-Birn)
      Schedule: Mo 14:00-16:00, Mi 12:00-14:00 (Class starts on: 2024-10-14)
      Location: T9/Gr. Hörsaal (Takustr. 9)

      Comments

      Website: https://www.mi.fu-berlin.de/w/SE/VorlesungNichtseq_Vert_Prg2021

       

      Contents:

      Programming and synchronization of concurrent processes that share resources or interact through message passing.

      • Non-Sequential programs and processes in their various forms, non-determinism, determinism
      • Synchronization mechanisms: locks, monitors, guards, events, semaphores
      • Non-Sequential program execution and object oriented systems
      • Control flow, strategies selection, priorities, handling and avoiding deadlock
      • Coroutines implementation, 
      • - Multiprocessor systems
      • Programming and Synchronisation of concurrent processes that interact through message passing
      • Remote Calling Techniques
      • Client-server, Peer-to-peer Networks
      • Parallel computing over networks
      • Concurrent and coordination languages
      • Processing on the server and on the client.
      • Middleware, structured communication, static and dynamic interfaces
      • Event-based and stream-based processing
      • Security of network applications
      • Non-functional Aspects (time, memory, quality of service)

      Suggested reading

      Literatur:

      • Principles of Concurrent and Distributed Programming. M. Ben-Ari. Addison-Wesley. 
      • Distributed Systems. Concepts and Design. Fifth Edition. George Coulouris, Jean Dollimore, Tim Kindberg, Gordon Blair. Pearson.

    • 19322102 Practice seminar
      Practice seminar for Concurrent and Distributed Programming (Barry Linnert)
      Schedule: Mo 10:00-12:00, Mo 12:00-14:00, Di 10:00-12:00, Di 12:00-14:00, Di 14:00-16:00, Do 10:00-12:00, Do 12:00-14:00, Do 14:00-16:00 (Class starts on: 2024-10-21)
      Location: T9/051 Seminarraum (Takustr. 9)
  • Network Programming

    0086bA1.5
    • 19322101 Lecture
      Concurrent, Parallel, and Distributed Programming (Barry Linnert, Claudia Müller-Birn)
      Schedule: Mo 14:00-16:00, Mi 12:00-14:00 (Class starts on: 2024-10-14)
      Location: T9/Gr. Hörsaal (Takustr. 9)

      Comments

      Website: https://www.mi.fu-berlin.de/w/SE/VorlesungNichtseq_Vert_Prg2021

       

      Contents:

      Programming and synchronization of concurrent processes that share resources or interact through message passing.

      • Non-Sequential programs and processes in their various forms, non-determinism, determinism
      • Synchronization mechanisms: locks, monitors, guards, events, semaphores
      • Non-Sequential program execution and object oriented systems
      • Control flow, strategies selection, priorities, handling and avoiding deadlock
      • Coroutines implementation, 
      • - Multiprocessor systems
      • Programming and Synchronisation of concurrent processes that interact through message passing
      • Remote Calling Techniques
      • Client-server, Peer-to-peer Networks
      • Parallel computing over networks
      • Concurrent and coordination languages
      • Processing on the server and on the client.
      • Middleware, structured communication, static and dynamic interfaces
      • Event-based and stream-based processing
      • Security of network applications
      • Non-functional Aspects (time, memory, quality of service)

      Suggested reading

      Literatur:

      • Principles of Concurrent and Distributed Programming. M. Ben-Ari. Addison-Wesley. 
      • Distributed Systems. Concepts and Design. Fifth Edition. George Coulouris, Jean Dollimore, Tim Kindberg, Gordon Blair. Pearson.

    • 19322102 Practice seminar
      Practice seminar for Concurrent and Distributed Programming (Barry Linnert)
      Schedule: Mo 10:00-12:00, Mo 12:00-14:00, Di 10:00-12:00, Di 12:00-14:00, Di 14:00-16:00, Do 10:00-12:00, Do 12:00-14:00, Do 14:00-16:00 (Class starts on: 2024-10-21)
      Location: T9/051 Seminarraum (Takustr. 9)
  • Computer Architecture

    0086bA2.2
    • 19300601 Lecture
      Computer Architecture (Larissa Groth)
      Schedule: Fr 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-18)
      Location: T9/Gr. Hörsaal (Takustr. 9)

      Comments

      The module Computer Architecture covers basic concepts of computer systems. Topics are von-Neuman/Harvard architecture, microarchitectures, RISC/CISC, micro programming, pipelining, caches, memory hierarchy, bus systems, assembler programming, multi processor systems, branch prediction, representation of numbers and other data types, computer arithmetic.

      Suggested reading

      • Andrew S. Tannenbaum: Computerarchitektur, 5.Auflage, Pearson Studium, 2006
      • English: Andrew S. Tanenbaum (with contributions from James R. Goodman):
      • Structured Computer Organization, 4th Ed., Prentice Hall International, 2005.

    • 19300604 PC-based Seminar
      Practice seminar for Computer Architecture (Larissa Groth)
      Schedule: Di 10:00-12:00, Di 12:00-14:00, Di 14:00-16:00, Mi 12:00-14:00, Mi 14:00-16:00, Do 10:00-12:00, Do 12:00-14:00, Do 14:00-16:00, Fr 12:00-14:00 (Class starts on: 2024-10-15)
      Location: T9/K 038 Rechnerpoolraum (Takustr. 9)
  • Operating Systems

    0089cA3.1
    • 19312101 Lecture
      Systems Software (Barry Linnert)
      Schedule: Mo 10:00-12:00, Do 12:00-14:00 (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
  • 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)
  • Fundamentals of Theoretical Computer Science

    0086bA3.1
    • 19301201 Lecture
      Foundations of Theoretical Computer Science (Katharina Klost, Wolfgang Mulzer)
      Schedule: Mo 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-14)
      Location: T9/Gr. Hörsaal (Takustr. 9)

      Comments

      Contents:

      • models of computation
        • automata
        • formal languates
        • grammars and the Chomsky-hierarchy
        • Turing-machines
        • computabilty
      • introduction to the complexity of computational problems

      Suggested reading

      • Uwe Schöning, Theoretische Informatik kurzgefasst, 5. Auflage, Spektrum Akademischer Verlag, 2008
      • John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman, Einführung in die Automatentheorie, Formale Sprachen und Komplexität, Pearson Studium, 3. Auflage, 2011
      • Ingo Wegener: Theoretische Informatik - Eine algorithmenorientierte Einführung, 2. Auflage, Teubner, 1999
      • Michael Sipser, Introduction to the Theory of Computation, 2nd ed., Thomson Course Technology, 2006
      • Wegener, Kompendium theoretische Informatik - Eine Ideensammlung, Teubner 1996

    • 19301202 Practice seminar
      Practice seminar for Foundations of Theoretical Computer Science (Katharina Klost)
      Schedule: Di 08:00-10:00, Di 10:00-12:00, Di 12:00-14:00, Di 16:00-18:00, Mi 10:00-12:00, Mi 12:00-14:00, Mi 14:00-16:00 (Class starts on: 2024-10-15)
      Location: A6/SR 025/026 Seminarraum (Arnimallee 6)
  • Software Project

    0086bA3.4
    • 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.

    • 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.

    • 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

  • Practices in Professional Software Development

    0089cA1.22
    • 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

    0089cA1.27
    • 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
      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: Mo 14:00-16:00, Di 12:00-14:00 (Class starts on: 2024-10-14)
      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
      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: -
      Location: keine Angabe
    • 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

    0089cA1.28
    • 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
      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: Mo 14:00-16:00, Di 12:00-14:00 (Class starts on: 2024-10-14)
      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
      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: -
      Location: keine Angabe
    • 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 (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)
  • 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)
  • Analysis I

    0084dA1.1
    • 19202801 Lecture
      Analysis I (Marita Thomas)
      Schedule: Di 10:00-12:00, Do 10:00-12:00 (Class starts on: 2024-10-15)
      Location: T9/Gr. Hörsaal (Takustr. 9)

      Comments

      Content:
      This is the first part of a three semester introduction into the basic mathematical field of Analysis. Differential and integral calculus in a real variable will be covered. Topics:

      1. fundamentals, elementary logic, ordered pairs, relations, functions, domain and range of a function, inverse functions (injectivity, surjectivity)
      2. numbers, induction, calculations in R, C
      3. arrangement of R, maximum and minimum, supremum and infimum of real sets, supremum / infimum completeness of R, absolute value of a real number, Q is dense in R
      4. sequences and series, limits, Cauchy sequences, convergence criteria, series and basic principles of convergence
      5. topological aspects of R, open, closed, and compact real sets
      6. sequences of functions, series of functions, power series
      7. properties of functions, boundedness, monotony, convexity
      8. continuity, limits and continuity of functions, uniform continuity, intermediate value theorems, continuity and compactness
      9. differentiability, concept of the derivative, differentiation rules, mean value theorem, local and global extrema, curvature, monotony, convexity
      10. elementary functions, rational functions, root functions, exponential functions, angular functions, hyperbolic functions, real logarithm, inverse trigonometric functions, curve sketching
      11. beginnings of integral calculus

      Suggested reading

      Literature:

      • Bröcker, Theodor: Analysis 1, Spektrum der Wissenschaft-Verlag.
      • Forster, Otto: Analysis 1, Vieweg-Verlag.
      • Spivak, Michael: Calculus, 4th Edition.

      Viele Analysis Bücher sind auch über die Fachbibliothek der FU Berlin elektronisch verfügbar.

      Bei Schwierigkeiten mit den Grundbegriffen Menge, Abbildung etc. ist die folgende Ausarbeitung empfehlenswert:

    • 19202802 Practice seminar
      Tutorial: Analysis I (Marita Thomas)
      Schedule: Mi 12:00-14:00, Mi 14:00-16:00, Mi 16:00-18:00, Fr 08:00-10:00 (Class starts on: 2024-10-16)
      Location: A7/SR 140 Seminarraum (Hinterhaus) (Arnimallee 7)
  • Linear Algebra I

    0084dA1.4
    • 19201401 Lecture
      Linear Algebra I (Alexander Schmitt)
      Schedule: Mo 08:00-10:00, Mi 08:00-10:00 (Class starts on: 2024-10-16)
      Location: A3/Hs 001 Hörsaal (Arnimallee 3-5)

      Comments

      Content:

      • Basic terms/concepts: sets, maps, equivalence relations, groups, rings,
      • fields
      • Linear equation systems: solvability criteria, Gauss algorithm
      • Vector spaces: linear independence, generating systems and bases, dimension,
      • subspaces, quotient spaces, cross products in R3
      • Linear maps: image and rank, relationship to matrices, behaviour under
      • change of basis
      • Dual vector spaces: multilinear forms, alternating and symmetric bilinear
      • forms, relationship to matices, change of basis
      • Determinants: Cramer's rule, Eigenvalues and Eigenvectors


      Prerequisites:

      Participation in the preparatory course (Brückenkurs) is highly recommended.

       

      Suggested reading

      • Siegfried Bosch, Lineare Algebra, 4. Auflage, Springer-Verlag, 2008;
      • Gerd Fischer, Lernbuch Lineare Algebra und Analytische Geometrie, Springer-Verlag, 2017;
      • Bartel Leendert van der Waerden, Algebra Volume I, 9th Edition, Springer 1993;

      Zu den Grundlagen

      • Kevin Houston, Wie man mathematisch denkt: Eine Einführung in die mathematische Arbeitstechnik für Studienanfänger, Spektrum Akademischer Verlag, 2012

    • 19201402 Practice seminar
      Practice seminar for Linear Algebra I (Alexander Schmitt)
      Schedule: Mo 10:00-12:00, Mo 16:00-18:00, Mi 10:00-12:00, Fr 14:00-16:00 (Class starts on: 2024-10-14)
      Location: A3/SR 119 (Arnimallee 3-5)
  • Analysis

    0086bA4.2
    • 19301101 Lecture
      Analysis for Computer Science and Bioinformatics (Katinka Wolter)
      Schedule: Mi 10:00-12:00, Fr 10:00-12:00 (Class starts on: 2024-10-16)
      Location: T9/Gr. Hörsaal (Takustr. 9)

      Additional information / Pre-requisites

      The sign-up for the tutorial sessions will be announced in due time.

      Comments

      Contents:

      • number systems: from natural numbers to real numbers, completeness property of the reals
      • polynomials: roots of polynomials, polynomial interpolation, rational functions
      • special functions:  exponential function, logarithm, trigonometric functions
      • complex numbers: exponential function for complex numbers, complex roots
      • convergence of sequences and series, convergence of functions, continuous functions, O-notation
      • differential calculus: derivative of a function,  interpretations and applications of the derivative
      • intergral calculus: primitive functions, definite integrals,  fundamental theorem of calculus, applications
      • power series
      • basics of stochastics: probability spaces, discrete and continuous random variables, expected value and variance of random variables

      Suggested reading

      • Kurt Meyberg, Peter Vachenauer: Höhere Mathematik 1, Springer-Verlag, 6. Auflage 2001
      • Dirk Hachenberger: Mathematik für Informatiker, Pearson 2005
      • Peter Hartmann: Mathematik für Informatiker, Vieweg, 4. Auflage 2006
      • Thomas Westermann: Mathematik für Ingenieure mit Maple 1, Springer-Verlag, 4. Auflage 2005

    • 19301102 Practice seminar
      Practice seminar for Analysis for Computer Science (Katinka Wolter)
      Schedule: -
      Location: keine Angabe
  • Specialization Module I (Seminar)

    0086bA5.12
    • 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.

  • Specialization Module (Project 4 hrs/wk)

    0086bA5.13
    • 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.

    • 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.

  • Specialization Module I (Project 4 hrs/wk)

    0086bA5.23
    • 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.

    • 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.

  • Specialization Module (Seminar)

    0086bA5.4
    • 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.

  • Project Seminar: Data Management Systems

    0089bA1.13
    • 19303811 Seminar
      Project Seminar: Data Management (Muhammed-Ugur Karagülle, Agnès Voisard)
      Schedule: Do 12:00-14:00 (Class starts on: 2024-10-17)
      Location: A6/SR 009 Seminarraum (Arnimallee 6)

      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

    0089bA1.17
    • 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

    0089bA1.18
    • 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

    0089bA1.21
    • 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

    0089bA1.24
    • 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

    0089bA1.26
    • 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/K 040 Multimediaraum (Takustr. 9)
  • Seminar: Database Systems

    0089bA1.33
    • 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

    0089bA1.35
    • 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

    0089bA1.36
    • 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

    0089bA1.4
    • 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

    0089bA1.49
    • 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.

  • 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
  • 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). 

       

  • Seminar: Mathematics

    0084cB1.1
    • 19202211 Seminar
      Seminar Discrete Mathematics I (Tibor Szabo)
      Schedule: Mo 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-08)
      Location: T9/046 Seminarraum (Takustr. 9)

      Comments

      This seminar will carry out a more specific study of some of the concepts of enumerative combinatorics and discrete structures that were introduced in the lecture Discrete Mathematics I.

    • 19203311 Seminar
      Proseminar/Seminar Gruppentheorie (N.N.)
      Schedule: -
      Location: keine Angabe

      Additional information / Pre-requisites

      Participants should feel comfortable with the contents of 'Linear algebra 1', and perhaps 'Linear algebra 2'. If there are interested students who have already done the 'Algebra und Zahlentheorie' module, we will also be able to find interesting topics for them.

      Comments

      In this (pro)seminar we will recapitulate the basics of group theory and study a few deeper properties and theorems. Possible topics are: solvable groups, nilpotent groups, representations of finite groups, the theorem of Schur-Zassenhaus, the theorems of P. Hall.

  • Discrete Mathematics I

    0084cB3.2
    • 19202001 Lecture
      Discrete Geometrie I (Georg Loho)
      Schedule: Di 10:00-12:00, Mi 10:00-12:00 (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)
    • Functional Programming 0086bA1.1
    • Object-Oriented Programming 0086bA1.2
    • Data Structures and Data Abstraction 0086bA1.3
    • Fundamentals of Computer Systems 0086bA2.1
    • Operating and Communication Systems 0086bA2.3
    • Computer Engineering Lab 0086bA2.4
    • Selected Topics in Technical Computer Science 0089cA3.12
    • Microprocessor Lab 0089cA3.2
    • Mobile Communications 0089cA3.3
    • Proseminar: Computer Science 0086bA3.2
    • Database Systems 0086bA3.3
    • Model-driven Software Development 0089cA1.11
    • Computer Security 0089cA1.16
    • Compiler Construction 0089cA1.19
    • Computer Graphics 0089cA1.2
    • Fundamentals of Software Testing 0089cA1.7
    • Model Checking 0089cA2.2
    • Computational Geometry 0089cA2.4
    • Analysis I 0084aA1.1
    • Linear Algebra I 0084aA2.1
    • Logic and Discrete Mathematics 0086bA4.1
    • Linear Algebra 0086bA4.4
    • Specialization Module (Lecture 4+2 hrs/wk) 0086bA5.1
    • Specialization Module II (Lecture 2+2 hrs/wk) 0086bA5.10
    • Specialization Module I (Lecture 2 hrs/wk) 0086bA5.11
    • Specialization Module II (Lecture 4+2 hrs/wk) 0086bA5.14
    • Specialization Module III (Lecture 4+2 hrs/wk) 0086bA5.15
    • Specialization Module IV (Lecture 2+2 hrs/wk) 0086bA5.16
    • Specialization Module (Lecture 2+2 hrs/wk, MiniProject) 0086bA5.17
    • Specialization Module I (Lecture 2+2 hrs/wk, MiniProject) 0086bA5.18
    • Specialization Module (incl. Project 2 hrs/wk, 3 CP) 0086bA5.19
    • Specialization Module (Lecture 2+2 hrs/wk) 0086bA5.2
    • Specialization Module I (incl. Project 2 hrs/wk, 3 CP) 0086bA5.20
    • Specialization Module (incl. Project, 3 CP) 0086bA5.21
    • Specialization Module I (incl. Project, 3 CP) 0086bA5.22
    • Specialization Module II (Lecture 2 hrs/wk, 3 CP) 0086bA5.24
    • Specialization Module (Lecture 2+1 hrs/wk, 4 CP) 0086bA5.25
    • Specialization Module (Lecture 2+2 hrs/wk, 6 CP) 0086bA5.26
    • Specialization Module (Lecture 3+1 hrs/wk, 7 CP) 0086bA5.27
    • Specialization Module (Lecture 3+2 hrs/wk, 9 CP) 0086bA5.28
    • Specialization Module I (Lecture 2+1 hrs/wk, 4 CP) 0086bA5.29
    • Specialization Module (Lecture 2 hrs/wk) 0086bA5.3
    • Specialization Module I (Lecture 2+2 hrs/wk, 6 CP) 0086bA5.30
    • Specialization Module I (Lecture 3+1 hrs/wk, 7 CP) 0086bA5.31
    • Specialization Module I (Lecture 3+2 hrs/wk, 9 CP) 0086bA5.32
    • Specialization Module (Lab/Project 2 hrs/wk) 0086bA5.5
    • Specialization Module (Lab/Project 3 hrs/wk) 0086bA5.6
    • Specialization Module (Lab/Project 4 hrs/wk) 0086bA5.7
    • Specialization Module (Lecture 4+2 hrs/wk) 0086bA5.8
    • Specialization Module IV (Lecture 2+2 hrs/wk) 0086bA5.85
    • Specialization Module (4+2 hrs/wk, 10 CP) 0086bA5.86
    • Specialization Module I (4+2 hrs/wk, 10 CP) 0086bA5.87
    • Specialization Module (Seminar, 5 CP) 0086bA5.88
    • Specialization Module I (Seminar, 5 CP) 0086bA5.89
    • Specialization Module (Lecture 4+2 hrs/wk) 0086bA5.9
    • Specialization Module (2 hrs/wk Lab, 4 CP) 0086bA5.90
    • Specialization Module I (2 hrs/wk Lab, 4 CP) 0086bA5.91
    • Specialization Module (Lecture 2 + lab 2 hrs/wk, 5 CP) 0086bA5.92
    • Specialization Module I (Lecture 2 + lab 2 hrs/wk, 5 CP) 0086bA5.93
    • 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
    • Database Technology 0089bA1.5
    • Empirical Evaluation in Computer Science 0089bA1.6
    • Advanced Aspects of Functional Programming 0089bA1.7
    • Computer Security 0089bA1.8
    • Artificial Intelligence 0089bA1.9
    • Software Project: Application of Algorithms 0089bA2.11
    • Computational Geometry 0089bA2.2
    • 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
    • Microprocessor Lab 0089bA3.2
    • Project Management 0089bA4.25
    • Starting a Business in IT 0089bA4.27
    • Digital Video 0089bA4.5
    • E-Learning Platforms 0089bA4.6
    • Medical Image Processing 0089bA4.9
    • Elementary Geometry 0082aB1.3
    • Analysis II 0084aA1.2
    • Linear Algebra II 0084aA2.2
    • Computer-Oriented Mathematics I 0084aA3.1
    • Computer-Oriented Mathematics II 0084aA3.2
    • Introduction to Numerical Mathematics (Numerical Mathematics I) 0084aA4.1
    • Introduction to Probability and Statistics (Probability and Statistics I) 0084aA4.2
    • Introduction to Elementary Probability and Statistics 0084bA4.2
    • Algorithmische Bioinformatik 0260aA1.4
    • Statistics I for Students of Life Sciences 0260aA2.5
    • Physics for Biology, Geosciences, Computer Science and Mathematics 0086bK3.1
    • Physics Internship for Geo-Sciences, Computer Science and Mathematics 0086bK3.2
    • Additional Courses in Computer Science 0086bL1.1