Computer Science

• Gesamtes Lehrangebot der Informatik

  E24nA1.1
  • 19000546 Mentoring
    Mentoring (Ulrike Seyferth)
    Schedule: Termine siehe LV-Details (Class starts on: 2024-09-12)
    Location: A6/SR 031 Seminarraum (Arnimallee 6)
    

    Comments

    The mentoring program offers events and counseling services primarily (but not only!) for first-year students. All offers are voluntary and are based on your needs and wishes!

    If you have questions or wishes, please contact us!

    Your mentors in mathematics, computer science and bioinformatics

  • 19300001 Lecture
    Fundamentals of Programming (Wolfgang Mulzer)
    Schedule: Mo 14:00-16:00, Mi 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-14)
    Location: Gr. Hörsaal (Raum B.001) (Arnimallee 22)
    

    Comments

    Qualification goals 

    The students can explain and compare different programming paradigms. They are able to interpret descriptions and source code related to fundamental data structures, to characterize how they work, and to implement basic algorithms and data structures in different programming paradigms, adapting them to given requirements. They can discuss the advantages and disadvantages of different solutions for algorithmic problems.

    Contents

    Students acquire the fundamentals of programming. We will discuss basic programming paradigms, such as imperative, functional, and object oriented. Students will learn about expressions and data types, as well as fundamental aspects of imperative programming (e.g., state, statements, control structures, input-output), and practice their application. Students will also gain an understanding of fundamental aspects of functional programming (functions, recursion, higher-order functions, currying), object-oriented concepts such as encapsulation and inheritance, polymorphism, as well as basic algorithmic tasks (e.g., searching, sorting, selection, and simple array- and pointer-based data structures), and practice their implementation.

  • 19300002 Practice seminar
    Practice seminar for Fundamentals of Programming (N.N.)
    Schedule: Mo 08:00-10:00, Mo 10:00-12:00, Mo 16:00-18:00, Di 08:00-10:00, Di 12:00-14:00, Di 16:00-18:00, Mi 10:00-12:00, Mi 14:00-16:00, Mi 16:00-18:00, Do 16:00-18:00 (Class starts on: 2024-10-14)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Comments

    Tutorien finden erst ab der 2. Vorlesungswoche statt

  • 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)
    
  • 19300901 Lecture
    Discrete Structures for Computer Science (Katharina Klost)
    Schedule: Di 14:00-16:00, Do 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-15)
    Location: Elisabeth-Schiemann-Hörsaal (R 014) (Königin-Luise-Str. 12 / 16)
    

    Comments

    Qualifikationsziele

    Die Studierenden formulieren³ Aussagen formal aussagenlogisch und prädikatenlogisch. Sie analysieren⁴ und vereinfachen³ die logische Struktur gegebener Aussagen und beschreiben⁴ die logische Struktur von Beweisen. Sie benennen Eigenschaften unterschiedlicher Mengen, Relationen und Funktionen und begründen⁴ diese mit Hilfe formaler Argumente. Sie können Beweise für elementare Aussagen unter Verwendung elementarer Beweistechniken entwickeln⁵ und die Mächtigkeit von Mengen mit Hilfe kombinatorischer Techniken sowie Wahrscheinlichkeiten von Zufallsereignissen bestimmen³. Sie sind in der Lage, Fragestellungen der (Bio-)Informatik mit Hilfe der Graphentheorie und der diskreten Wahrscheinlichkeitstheorie zu modellieren.^3. Die Studierenden benennen Eigenschaften unterschiedlicher Graphen und begründen⁴ diese mit Hilfe formaler Argumente.

    Inhalte

    Studierende erlernen grundlegende Konzepte der Mengenlehre, Logik, Booleschen Algebra, Kombinatorik und Graphentheorie und üben deren Anwendung. Sie erarbeiten sich in der Mengenlehre Mengen, Relationen, Äquivalenz- und Ordnungsrelationen und Funktionen. Im Bereich der Logik und Booleschen Algebra erarbeiten sie sich Aspekte der Aussagenlogik, Prädikatenlogik, Erfüllbarkeitstests, sowie Boolesche Funktionen und Normalformen. Im Themenfeld Kombinatorik erlernen und diskutieren sie das Schubfachprinzip, Rekursion, Abzählprinzipien, Fakultät und Binomialkoeffizienten. Im Themenfeld Graphentheorie erarbeiten sie Repräsentationsformen, Wege, Kreise und Bäume. Zuletzt erarbeiten sie sich verschiedene Beweistechniken und grundlegende Aspekte Diskreter Wahrscheinlichkeitstheorie. Die meisten dieser Konzepte werden an Rechen- oder Beweisaufgaben geübt.

  • 19300902 Practice seminar
    Practice seminar for Discrete Structures for CS (Katharina Klost)
    Schedule: Mo 10:00-12:00, Mo 12:00-14:00, Mo 16:00-18:00, Di 08:00-10:00, Di 12:00-14:00, Di 16:00-18:00, Mi 10:00-12:00, Mi 14:00-16:00, Mi 16:00-18:00, Do 16:00-18:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-02)
    Location: T9/053 Seminarraum (Takustr. 9)
    
  • 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
    
  • 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)
    
  • 19301301 Lecture
    Consequences of Computer Science (Lutz Prechelt)
    Schedule: Do 12:00-14:00 (Class starts on: 2024-10-17)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Additional information / Pre-requisites

    The course language is German, including all slides and practice sheets.

    Homepage

    http://www.mi.fu-berlin.de/w/SE/TeachingHome

    Comments

    This course deals with the consequences of computer science. Its aim is to establish an understanding of the fact that computer systems intervene in manifold ways in our private and professional lifes and shapen them. Many of these influences bring about major risks and need a conscious and enlightened composition in which computer scientists by nature play an important role -- or should at least do so.

    We will for example have a look at how computerisation influences our private sphere, economics and society as a whole, our security and working environment. A conceptual introduction will provide orientational knowledge besides basic knowledge (Verfügungswissen) and strategies how to deal with both: analyse critically and get involved in the technical development.

    Suggested reading

    See the slides.

  • 19301302 Practice seminar
    Exercise for Consequences of Computer Science (Lutz Prechelt, Linus Ververs)
    Schedule: Mo 16:00-18:00, Di 08:00-10:00, Di 10:00-12:00, Di 12:00-14:00, Mi 14:00-16:00, Mi 16:00-18:00, Do 08:00-10:00, Do 10:00-12:00, Fr 12:00-14:00 (Class starts on: 2024-10-14)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Comments

    siehe Vorlesung; Informationen zu den Zeiten und Orten der täglichen Übungen sind zu finden auf der Veranstaltungswebseite

  • 19301710 Proseminar
    Undergraduate Seminar: Coding Theory (Max Willert)
    Schedule: Di 14:00-16:00 (Class starts on: 2024-10-15)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    Contents

    The proseminar delves more deeply into topics covered in the basic classes taught by the theory group. During the winter semester 2024/25, we consider the theory of coding.

    Prerequisites

    "Discrete Structures", "Linear Algebra" and "Algorithms and Data Structures"

    Suggested reading

    wird mit der Ankündigung bekannt gegeben

  • 19302201 Lecture
    System Administration (Rolf Dietze)
    Schedule: Termine siehe LV-Details (Class starts on: 2025-02-22)
    Location: A6/SR 031 Seminarraum (Arnimallee 6)
    

    Additional information / Pre-requisites

    The class will be taught as a block course. Details will be announced in due time.

    Comments

    Contents

    • shell scripting from the viewpoint of system administration
    • planning and setting up a computer system while taking availability and maintainability into consideration (RAS-conditions)
    • redundancy in networking and storage
    • planning and setting up a redundant storage system (Raid-technologies and management)
    • system administration, security and user management, accounting and logging
    • managing configuration files and documentation
    • backups - strategies and technologies
    • planning and realization of networkwide services and resources (e.g. file services, print services, network information services)
    • implementation on different platforms (AIX, Solaris)
    • partitioning, virtualization and resource management on modern systems supporting logical partitioning
    • virtualization and resource management at the operating systems level (workload partitions, zones, jails)
    • qualitative comparison of partitioning and virtualization techniques on PowerPC and Sparc based UNI*-systems.
    • delegation of administration tasks with rolebased access (RBAC)
    • ethical and legal aspects when dealing with administrative privileges,
    • special aspects and procedures when dealing with personal information and security clearances when dealing with vital systems

    At the beginning of the class, we will refresh the necessary knowledge to participate in the practical exercises and we will set up a working environment in the context of the administration of a heterogeneous computer network. Previous experience is desirable.

  • 19302230 Internship
    Internship for System Administration (Rolf Dietze)
    Schedule: -
    Location: keine Angabe
    
  • 19302613 Lab Seminar
    Planning, Realisation and Analysis of a Tutorial (Nicolas Perkowski, Max Willert)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Die Anmeldung zu diesem Kurs erfolgte bereits im Juli 2024. Sollten Sie Interesse an diesem Kurs haben, schreiben Sie den Dozierenden bitte eine E-Mail.

    Comments

    In a preparatory colloquium, current teaching methods and advising for tutors are presented and discussed. This colloquium is specifically for students, which particularly want to guide exercise sessions as a tutor for the mathematics and computer science students. An interview with the selection committee will take place even during the holidays, in which will be decided about the suitability as a tutor.

    After successful aptitude assessment a tutorial about a subjects of a lecture of the first four semesters bachelor study, should be prepare, expose, documented and analyzed.

  • 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)
    
  • 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)
    
  • 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.

  • 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)
    
  • 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)
    
  • 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

  • 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.

  • 19306711 Seminar
    Seminar on Algorithms (Mahmoud Elashmawi)
    Schedule: Mi 14:00-16:00 (Class starts on: 2024-10-16)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Comments

    Contents

    Advanced topcis in algorithm design with a changing focus. The topic is determined newly in each semester. For example, we might consider algorithms for problems on graphs, such as connectivity, shortest paths, or network flows.

    Target audience

    Masters students in computer science and mathematics.

    Recommended prerequisites

    "Advanced algorithms" or a similar class.

    Suggested reading

    Spezialliteratur aus Zeitschriften

  • 19308312 Project Seminar
    Implementation Project: Applications of Algorithms (László Kozma)
    Schedule: Di 14:00-16:00 (Class starts on: 2024-10-08)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    

    Comments

    Contents

    We choose a typical application area of algorithms, usually for geometric problems, and develop software solutions for it, e.g., computer graphics (representation of objects in a computer, projections, hidden edge and surface removal, lighting, raytracing), computer vision (image processing, filtering, projections, camera calibration, stereo-vision) or pattern recognition (classification, searching).

    Prerequsitions

    Basic knowledge in design and anaylsis of algorithms.

    Suggested reading

    je nach Anwendungsgebiet

  • 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.

  • 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). 

     

  • 19311720 Course
    Work and Life Tools (Lutz Prechelt)
    Schedule: Mo 18:00-20:00 (Class starts on: 2024-10-14)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Duration

    The weekly lecture is of three hours length.

    Language

    The course language is German.

    Homepage

    http://www.inf.fu-berlin.de/w/SE/KursArbeitsUndLebensmethodik2022

     

    Comments

    Work and Life Tools

    In this course we will shed light on those questions which decisively influence a successful course of action in one's studies and profession and the success and contentment in private life.

    These are mostly less technical abilities but rather characteristics: purposefullness, self confidence, ability to concentrate and relax, decision-making ability, clear communication, self-perception, motivation, stamina.

    The purpose of this course is to trigger and improve a purposeful and self-motivated personal development.

    Furthermore, it is explained how and why great parts of the so-called soft skills arise almost independently when developing the above-mentioned abilities.

    This course is a seminar in the original sense: mainly a discussion in which each participant explores something on his/her own (in this case his/her own behavior). However, the format differs completely to what the title "Seminar" ususally suggests in Computer Science: there are no topics assigned, no presentations, no papers. It is about ...  (Es geht um Bildung, nicht um Ausbildung)

    The number of participants is limited; prior registration is necessary. The course requires study experience and therefor cannot be attended by first semesters.

    I expect an open and commited particpation of all particpants. The course demands only a moderate expenditure of time, but a considerable input of will power.

    Suggested reading

    wird in der Veranstaltung bekannt gegeben

  • 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)
    
  • 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.

  • 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)
    
  • 19312904 PC-based Seminar
    Practice seminar for Seminar: Basics of Computer Science Education (Ralf Romeike)
    Schedule: Do 12:00-14:00 (Class starts on: 2024-10-17)
    Location: Die Veranstaltung findet im Raum 016, Königin-Luise Str. 24-26 statt.
    

    Comments

    Begleitveranstaltung zur Vorlesung 19312901

  • 19312911 Seminar
    Seminar: Basics of Computer Science Education (Ralf Romeike)
    Schedule: Mi 10:00-12:00 (Class starts on: 2024-10-16)
    Location: keine Angabe
    

    Comments

    Refer to German description. Courses of Computer Science Education are part of the German teacher-training and held in German only.

  • 19313017 Seminar / Undergraduate Course
    Seminar/Proseminar: Agile methods and technical practices (Lutz Prechelt, Linus Ververs)
    Schedule: Mo 10:00-12:00 (Class starts on: 2024-10-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Website

    https://www.mi.fu-berlin.de/w/SE/SeminarAgil2024

    
    Lecturer

    Linus Ververs

    
    Language

    German (presentation can be held in English)

    
    Target group

    • Proseminar: Bachelor students who attend / have attended the module "Scientific Work in Computer Science" and apply the knowledge they have learned and work scientifically for the first time in this seminar.
    • Seminar: Advanced Bachelor students who attend the module as part of their specialization area or Master students

    
    Prerequisites

    It is strongly recommended that you have already attended the software engineering module. (If not, please contact the lecturer in advance).

    Comments

    More than 20 years after the first publication of the agile manifesto (https://agilemanifesto.org/iso/en/manifesto.html), agile software development is here to stay. At the very least, many companies are tempted by the promise of agile development and flat hierarchies. In this seminar, we will look at different agile methods (Scrum, Kanban, eXtreme Programming, etc.), how they are used in practice, where and why they are deviated from and the technical practices (pair programming, continuous integration, DevOps, etc.) that support the agile way of working.

    
    During this seminar, students are expected to conduct independent research on their chosen topic. Whether the course is booked as a seminar or proseminar has an influence on the requirements:

    • Seminar: Here, several good sources (5-10) are to be found and a summary of the results presented. The aim is to work out the current state of research on the basis of a selected research question, identify gaps and contradictions in the research and derive recommendations for practice.
    • Proseminar: A good source should be found and presented in detail. Other related works (1-3) should only be discussed in passing for comparison. In the scientific articles presented, the conclusions presented should be critically examined with regard to credibility and relevance.

    Suggested reading

    The articles available for selection can be found in the resources folder on the KVV page.

  • 19313273 Brückenkurs
    Preparatory Course for First Years Students of Computer Science and Bioinformatics (Max Willert)
    Schedule: Termine siehe LV-Details (Class starts on: 2024-09-30)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Additional information / Pre-requisites

    Der Brückenkurs richtet sich an alle Studienanfänger:innen in den Fächern Informatik und Bioinformatik.

    Comments

    Beginnst Du im Wintersemester Dein Studium an der FU Berlin? Ist Dein Studienfach Informatik oder Bioinformatik? Dann bist Du herzlich zu unserem Brückenkurs eingeladen! Der Brückenkurs findet in den letzten beiden Wochen vor Vorlesungsbeginn in zeitlicher Abstimmung mit den Orientierungswochen statt.

    Infos findest du auch auf den Seiten des Studentischen Beratungszentrums, s. Seite zum Studienstart.

    Mathematisch-logisches Denken ist für das Lösen von Problemen der Informatik essentiell. Da hinsichtlich dieser Voraussetzungen in den letzten Jahren in den Informatik-Anfängervorlesungen einige Defizite deutlich wurden, werden im Rahmen des Brückenkurses die wichtigsten mathematischen Grundlagen wiederholt. Schwerpunkte sind: elementare Mengenlehre, Relationen und Funktionen, logische Grundlagen, Umgang mit mathematischen Formeln.

  • 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.

  • 19315030 Internship
    Schulpraktische Studien Informatik II: Teaching Training (Ralf Romeike, Viktoriya Olari)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Target audience

    This course is aimed at master's students of computer science (teacher training related).

    Comments

    Courses of Computer Science Education are part of the German teacher-training and held in German only.

    Contents

    In the teaching internship, basic knowledge of educational science, psychology, social science and subject-related didactics, which has been taught in the bachelor's program as well as in the preparatory seminar, is translated into practical action.

    Subject-specific structuring, teaching sequences, introductions, motivation, interest, problem orientation, contextual reference, areas of competence and basic concepts of the educational standards, reflection, transfer, securing, documentation and assessment of learning development.

     

    Suggested reading

    Wird bekannt gegeben. / To be announced.

  • 19315120 Course
    Schulpraktische Studien Informatik III: Wrap-Up Seminar (Ralf Romeike)
    Schedule: Fr 12:00-16:00 (Class starts on: 2024-10-18)
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Target audience

    This course is suited for master's students of computer science (teacher training related).

     

    Participation requirements

    successful participation in preparatory seminar and teaching internship

    Comments

    Courses of Computer Science Education are part of the German teacher-training and held in German only.

    Contents

    This in-depth seminar offers the opportunity to reflect on the experiences from the teaching internship and to develop possible solutions for problematic teaching situations. Further teaching methods are being developed that enable independent, action-oriented and self-determined work. The students’ own attitudes towards school, the teaching profession and subject-specific teaching are to be critically reflected upon.

    The examination includes preparing a report in which the student reflects on selected topics of the preparatory seminar, the planning, implementation and evaluation of his/her own teaching.

    Suggested reading

    Wird bekannt gegeben. / To be announced.

  • 19315312 Project Seminar
    Software Project: Distributed Systems (Justus Purat)
    Schedule: Di 14:00-16:00 (Class starts on: 2024-10-15)
    Location: T9/053 Seminarraum (Takustr. 9)
    
  • 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)
    
  • 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)
    
  • 19315733 Professional Internship
    Internship in Industry (Volker Roth)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    at least six weeks (240 hours) outside the university

    Comments

    Contents

    Internships play an important role in the course of study in computer science and offer a perspective on possible future job opportunities for our students. The purpose of the internship is to get to know everyday life on the job and to apply the knowledge and skills acquired during the studies in practice.

    The classes that accompany the internship offer an opportunity for intense preparation and reflection. Students learn about the job market and about the application process and can share their practical experiences.

    Additionally, students learn to appreciate the soft skills necessary on the job, and to evaluate the relationship between a university education and on-the-job requirements.

    Suggested reading

    Exemplarische Praktikumsberichte sind beim Praktikumsbeauftragten einsehbar.

  • 19315970 Begrüßungs- und Abschlussveranstaltung
    Welcome for Undergraduate Students of Computer Sciences (Lutz Prechelt)
    Schedule: Mo 14.10. 10:00-12:00 (Class starts on: 2024-10-14)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Additional information / Pre-requisites

    This event will take place once a semester.

    Comments

    see german text

  • 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.

  • 19319612 Project Seminar
    Research Project: Innovative teaching and learning systems (Wolfgang Mulzer)
    Schedule: Di 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Comments

    Content

    In this software project we will develop new ideas and necessary features for the MVS and KVV systems in the form of new tools/components/modules. After a seminar-style introduction to the necessary technologies, we will specify the requirements and design solutions and then develop them. Good teamwork is required. The possibilities for improving both systems are varied and range from infrastucture to usability. There will be weekly meetings during the semester, at which teams will report on progress and discuss solutions.

  • 19319701 Lecture
    Scientific Work/Research in Computer Science (Volker Roth)
    Schedule: Mi 12:00-14:00 (Class starts on: 2024-12-11)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Comments

    The lecture introduces students to scientific work. The essential forms of written and oral knowledge representation are described. It explains how to write computer science texts and how to read and examine them. Furthermore, students will be introduced to legal, ethical and philosophical problems of the sciences and in particular of computer science. Furthermore, problems of gender and diversity in computer science and in lectures will be presented and solution strategies will be discussed.

  • 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
    
  • 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)
    
  • 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.

  • 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)
    
  • 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

  • 19325620 Course
    Introduction Seminar for Teaching Assistants (Ulrike Bücking)
    Schedule: Termine siehe LV-Details (Class starts on: 2024-09-23)
    Location: A3/ 024 Seminarraum (Arnimallee 3-5)
    

    Comments

    In this course future teaching assistants are been prepared for their work in the exercise courses. The following topics will be discussed:

    • techniques for the exercise course
    • activating and motivating students
    • types of preliminary discussing and debriefing of exercises
    • correcting exercises
    • converse with students and docents
    • self concept
    • gender & diversity
    • behaviour during exam supervision
    • dealing with sensitive data
    • introduction to KVV-system

  • 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.

  • 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)
    
  • 19328217 Seminar / Undergraduate Course
    Seminar/Proseminar: New Trends in Information Systems (Agnès Voisard, Muhammed-Ugur Karagülle)
    Schedule: Mi 10:00-12:00 (Class starts on: 2024-10-16)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Comments

    This seminar aims at studying recent trends in data management. Among others, we will look at two emerging topics, namely Location-Based Services (LBS) and Event-Based Services (EBS).

    Event-based Systems (EBS) are part of many current applications such as business activity monitoring, stock tickers, facility management, data streaming, or security. In the past years, the topic has gained increasing attention from both the industrial and the academic community. Current research concentrates of diverse aspects that range from event capture (incoming data) to response triggering. This seminar aims at studying some of the current trends in Event-based Systems with a strong focus on models and design. Location-based services are now often part of every day's life through applications such as navigation assistants in the public or private transportation domain. The underlying technology deals with many different aspects, such as location detection, information retrieval, or privacy. More recently, aspects such as user context and preferences were considered in order to send users more personalized information.

    A solid background in databases is required, typically a database course at a bachelor level.

    Suggested reading

    Wird bekannt gegeben.

  • 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.

  • 19328302 Practice seminar
    Data Visualization (Claudia Müller-Birn)
    Schedule: -
    Location: keine Angabe
    
  • 19328601 Lecture
    Cryptocurrencies and Blockchain (Katinka Wolter, Justus Purat)
    Schedule: Di 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Comments

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

    Suggested reading

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

  • 19328602 Practice seminar
    Practice Session on Cryptocurrencies (Justus Purat)
    Schedule: Do 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-09-27)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19329617 Seminar / Undergraduate Course
    Seminar/Proseminar: Telematics (Jochen Schiller)
    Schedule: -
    Location: keine Angabe
    

    Comments

    This seminar focuses on several aspects of technical Computer Science. At the start of the seminar you will receive a list of suggested topics that mainly deal with particular aspects of the so-called Trusted Computing and security issues in the Internet of Things. You are also very welcome to suggest your own research topic that is closely related to technical Computer Science. You can work on your topic exclusively or in a small group of 2-3 students. But then, it has to be apparent who contributed what part to the seminar paper.

     

    It is possible to combine this seminar with the software project Telematics. Then, the theoretical foundations of the topic are dealt with in the scientific seminar paper and implemented in practice in the software project. Please note that the seminar paper is not supposed to deal with details of the implementation and that you are still obliged to write an accurate documentation of the software project in written form. 

     

    Concerning the schedule: This seminar takes place during the semester. There are only a few meetings, but these are mandatory. On the first meeting (03.11.2020), the topic list will be handed out and discussed. Please prepare a short (2-3 minutes) overview of your own topic suggestion if you would like to include it in the seminar. On the next week (10.11.2020), the topics will be assigned. After that there will be 3 presentation dates in total: the topic presentation (01.12.2021), a short interim presentation (12.01.2021) and the final presentation (23.02.2021). There will be no further meetings beyond that. This semester, all meetings will take place as video conferences with Webex.

  • 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)
    
  • 19330212 Project Seminar
    Seminar: Introduction to Profile Areas Data Science (Katinka Wolter)
    Schedule: -
    Location: keine Angabe
    
  • 19330252 RV
    Introduction to Profile Areas Data Science (Katinka Wolter)
    Schedule: Fr 12:00-16:00 (Class starts on: 2024-10-18)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    
  • 19330313 Lab Seminar
    Programming for Data Science (Sandro Andreotti)
    Schedule: Mo 12:00-16:00 (Class starts on: 2024-10-28)
    Location: A3/SR 120 (Arnimallee 3-5)
    

    Comments

    Qualifikationsziele

    Die Studentinnen und Studenten haben ein tieferes Verständnis für Konzepte in der Programmierung mit einer höheren Programmiersprache (z. B. C/C++, Java oder Python).

    Inhalte:

    Einführung in verschiedene Arten von Programmiertechniken.

  • 19330401 Lecture
    Statistics for Data Science (Vesa Kaarnioja)
    Schedule: Mo 10:00-12:00 (Class starts on: 2024-10-14)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    

    Comments

    This course serves as an introduction to foundational aspects of modern statistical data analysis. Frequentist and Bayesian inference are presented from the perspective of probabilistic modelling.

    Details can be found on the website of the previous year.

  • 19330402 Practice seminar
    Practice Seminar Statistics for Data Sci (Vesa Kaarnioja)
    Schedule: Di 10:00-12:00 (Class starts on: 2024-10-15)
    Location: A7/SR 031 (Arnimallee 7)
    
  • 19330811 Seminar
    Seminar: digi4all (Ralf Romeike)
    Schedule: Di 15.10. 16:00-18:00 (Class starts on: 2024-10-15)
    Location: Virtueller Raum 01
    

    Additional information / Pre-requisites

    Target audience

    The digi4all seminar is open to anyone who wishes to acquire competencies for teaching and learning under the conditions of digitization in a self-determined way and who would like to get a comprehensive view of the opportunities and challenges of digitization for the education system.

    Comments

    Contents

    All subjects and their disciplines are experiencing strong changes due to digitalization. Therefore, students acquire comprehensive digital basic, application and reflection competencies within this course: they learn to deal with digital systems in a self-determined manner, to understand and explain them and to evaluate them with regard to interactions with individuals, society and the education system. Concepts for transferring what has been learned to teaching-learning processes establish the theoretically substantiated practical reference and enable adequate use of digital media as well as the design of contemporary teaching under the conditions of digitality.

    Seminar information

    digi4all takes place online and independent of time.

    Suggested reading

    Wird zu Beginn des Semesters bekannt gegeben. / To be announced at the beginning of the semester.

  • 19332270 Begrüßungs- und Abschlussveranstaltung
    Welcome event for students of msc data science (Katinka Wolter)
    Schedule: -
    Location: keine Angabe
    

    Comments

    This information session is aimed at master students in their first semester, especially those who did their bachelor's degree at another university (in Germany or a different country). Attendants will be provided with information on the organization and the content of their studies. Afterwards there will be the opportunity to talk to experienced master's students and get to know fellow students.

  • 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)
    
  • 19333002 Practice seminar
    Practice seminar for Cybersecurity and AI I (Gerhard Wunder)
    Schedule: -
    Location: keine Angabe
    
  • 19333311 Seminar
    Seminar: Continual Learning (Manuel Heurich)
    Schedule: Mo 10:00-12:00 (Class starts on: 2024-10-14)
    Location: A3/SR 115 (Arnimallee 3-5)
    

    Comments

    This seminar focuses on recent advances in unsupervised learning, an increasingly important field within machine learning. In unsupervised learning, we use the data itself rather than additional output labels to define a training objective, such as completing a given text sequence or filling in an image region. This way we can learn powerful representations, and stable generative paths. We will discuss new UL methods such as CLIP, DALLE, and FLAMINGO that combine language and image models in joint represenatations.

  • 19333417 Seminar / Undergraduate Course
    Seminar/Proseminar: Explainable AI for Data Science (Grégoire Montavon)
    Schedule: Di 14:00-16:00 (Class starts on: 2024-10-15)
    Location: KöLu24-26/SR 006 Neuro/Mathe (Königin-Luise-Str. 24 / 26)
    

    Comments

    Explainable AI is a recent and growing subfield of machine learning (ML) that aims to bring transparency into ML models without sacrificing their predictive accuracy. This seminar will explore current research on the use of Explainable AI for extracting insights from large datasets of interest. Use cases in biomedicine, chemistry and earth sciences will be covered.

    Students will select a few papers from a pool of thematically relevant research papers, which they will read and present over the course of the semester.

  • 19333611 Seminar
    Seminar Deep Learning for biomedical applications (Vitaly Belik)
    Schedule: Mo 16:00-18:00 (Class starts on: 2024-10-14)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Comments

    Recent developments in the area of machine learning due to availability of data and computational power promise to revolutionize almost every area of science. The driving technology behind this advancement is deep learning – a machine learning technology based on artificial neural networks consisting of many layers. Deep learning is capable of processing huge amount of data of different nature and already outperforming humans in many decision-making tasks. Biomedical research became now a source of large heterogeneous data, i.e. images, video, activity sensors, omics and text data. Leveraging the opportunities of this deep learning technology in the biomedical field requires particular set of skills combining thorough knowledge of necessary algorithms, specifics of biomedical data and designated programming tools. In this course we aim to offer students with background in computer science an opportunity to acquire the above skills to be able to deploy deep learning technology with a focus on biomedical applications. The course is structured as a seminar, where students under extensive guidance of instructors read fundamental books and recent research articles on deep learning, learn necessary programming tools, and produce their own implementations of computational pipelines in case studies using already published or original data. Starting from fundamental aspects of deep learning we aim to cover its applications to e.g. image data, time series data, text data, complex networks.

    Suggested reading

    [1] Andresen N, Wöllhaf M, Hohlbaum K, Lewejohann L, Hellwich O, Thöne- Reineke C, Belik V, Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expres- sion analysis. Plos One, 15(4):e0228059, (2020) https://doi.org/10.1371/ journal.pone.0228059

    [2] Jarynowski A, Semenov A, Kamiński M, Belik V. Mild Adverse Events of Sputnik V Vaccine in Russia: Social Media Content Analysis of Telegram via Deep Learning. J Med Internet Res 2021;23(11):e30529 https://doi.org//10.2196/30529

  • 19334212 Project Seminar
    Softwareproject: Machine Learning with Graphs for Improved (Cancer) Treatment (Pauline Hiort, Pascal Iversen)
    Schedule: Mi 14:00-16:00 (Class starts on: 2024-10-16)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    

    Comments

    In the software project, we will implement, train, and evaluate various machine learning (ML) methods. The focus of the project is on graph neural networks (GNNs) that use graphs as input features for learning. We will compare the GNNs with various baseline methods, such as neural networks and regression models. The different ML methods will be applied and evaluated on a specific dataset, such as predicting drug combinations for cancer treatment. We will prepare the dataset and analyze it using the implemented methods. The programming language is Python, and we plan to use modern Python modules for ML like scikit-learn, TensorFlow, or PyTorch. Good Python skills are required. The goal is to create a Python package that provides reusable code for preprocessing, training ML models, and evaluating results with documentation (e.g., using Sphinx) for the specific use case. The software project takes place throughout the semester and can also be conducted in English.

  • 19334412 Project Seminar
    SWP: Szenario-Management in the Future Security Lab (Larissa Groth)
    Schedule: Mi 14:00-16:00 (Class starts on: 2024-10-16)
    Location: K 063 Hardwarepraktikum (Takustr. 9)
    

    Comments

    The BeLIFE project, part of the working group Telematics & Computer Systems, focuses on improving knowledge transfer and communication in civil security research. A central component of the project is the Future Security Lab, located at the Einstein Center Digital Future (ECDF) in Mitte. The lab welcomes politicians from federal and state levels, as well as representatives from authorities and organizations with security responsibilities.

    Within the software project, students develop concepts to optimize and creatively enhance the existing technical infrastructure of the space. The goal is to increase the usability of the space for scientists and improve the user experience for visitors. To achieve this, the software project consists of several sub-areas, either arising from a specific problem to be solved or requiring creative approaches and ingenuity. Tasks include system administration, interface development, as well as light/sound installation and orchestration. Examples of challenges include the parallel startup of all computers in a network via WakeOn LAN from a web app or optimizing the existing web app for scenario presentation.

    The tasks are exclusively addressed in small groups (3-5 students). Collaboration and code availability are facilitated through the department's own GitLab or a public GitHub. Results should be well-documented, for example, through README files in Git and a well-structured wiki. Modularity and expandability of the developed code, along with thorough documentation, are crucial for the success of this software project!

    Regarding the process, this software project takes place throughout the semester. There are a few mandatory large group meetings with all participants. In addition, there are short weekly meetings where at least one group member reports on the current status. The first meeting (October 16, 2024) will be held in Berlin Mitte at the Future Security Lab, Wilhelmstr. 67, 10117 Berlin. During this session, already implemented solutions will be presented, and issues will be discussed. There are a total of three presentation dates: the presentation of an initial approach to problem-solving (November 13, 2024), a brief interim presentation (December 18, 2024), and the final presentation (Februrary 12, 2025).

    Students also regularly have the opportunity to work in the Future Security Lab premises, familiarize themselves with the equipment, and conduct tests.

  • 19334617 Seminar / Undergraduate Course
    Seminar/Proseminar: Multi-Agent Reinforcement Learning (Tim Landgraf)
    Schedule: Mo 10:00-12:00 (Class starts on: 2024-10-14)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

    Comments

    This seminar provides an exploration of large language models (LLMs), covering both foundational concepts and the latest advancements in the field. Participants will gain a comprehensive understanding of the architecture, training, and applications of LLMs, based on seminal research papers. The course will be organised as a journal club: students present individual papers, which are then discussed in the group to make sure we all get the ideas presented.

    ### Potential Topics

       - Neural networks and deep learning basics

       - Sequence modeling and RNNs (Recurrent Neural Networks)

       - Vaswani et al.'s "Attention is All You Need" paper

       - Self-attention mechanism

       - Multi-head attention and positional encoding

       - GPT-1: Radford et al.'s pioneering work

       - GPT-2: Scaling and implications

       - GPT-3: Architectural advancements and few-shot learning

       - BERT (Bidirectional Encoder Representations from Transformers)

       - T5 (Text-To-Text Transfer Transformer)

       - DistilBERT and efficiency improvements

       - Mamba:l and other SSMs: Design principles and performance

       - Flash Attention et al: Improving efficiency and scalability

       - Training regimes and resource requirements

       - Fine-tuning and transfer learning

    - Emergence of new capabilities

  • 19334717 Seminar / Undergraduate Course
    Seminar/Proseminar: Machine Learning for Process Control (Grégoire Montavon)
    Schedule: Do 14:00-16:00 (Class starts on: 2024-10-17)
    Location: KöLu24-26/SR 006 Neuro/Mathe (Königin-Luise-Str. 24 / 26)
    

    Comments

    Numerous real-world processes need to be kept under control in order to ensure safety or efficiency. Machine learning models are good candidates for this. They can for example detect shifts/anomalies/decalibrations/instabilities/etc. and possibly also predict which action needs to be taken on the process. The real-time nature of such tasks brings unique challenges from a ML perspective compared to classical application of ML. This seminar will explore relevant ML methods such as online/reinforcement learning and real-time data analysis. Use cases in manufacturing and intensive care will be covered. Students will select a few papers from a pool of thematically relevant research papers, which they will read and present over the course of the semester.

  • 19334806 Seminar-style instruction
    Project management in agile environments part 1 (Lutz Prechelt, Matthias Horn)
    Schedule: Mo 08:30-10:00, Fr 16:00-18:00 (Class starts on: 2024-10-14)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Comments

    Goals: The students understand several different models of scaled agile software development, that is, agile development encompassing multiple cooperating teams. They understand basic and intermediate methods of hybrid, predictive, and adaptive project management in such agile environments and are able to apply them. They can design a project plan and validate it with suitable methods. They can participate in the project management team of such a hybrid effort and take responsibility for substantial parts of the project management, including managing staff. They can lead a simple project alone.

  • 19334910 Proseminar
    PS: Methods for the analysis of graphs and networks (Katharina Baum, Pauline Hiort, Pascal Iversen)
    Schedule: Di 16:00-18:00 (Class starts on: 2024-10-15)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    

    Comments

    The world is complex, and so is its data. Graphs (or networks) are key for the analysis of complex data and in the integration of data layers. They allow mapping and formal investigation of relationships between entities (nodes).

    In the course of the seminar, we will explore different computational analysis methods of graphs and networks. We will learn about different types and properties of graphs and how to deal with them in general. In addition, application areas of graphs such as social or biological networks will be discussed.

    Examples for specific topics are

    • Basic properties of graphs and nodes and how to determine them: shortest paths, centralities, degree distribution, clustering coefficients
    • The small-world property of social interaction networks
    • Clusters and communities in networks
    • Application: Networks for mapping molecular regulations
    • Random graphs and their application
    • Working with large networks, representative subgraphs
    • Modeling information and signal flow in graphs and detecting signal sources
    • Nodes as vectors - graph-based embedding methods

  • 19335011 Seminar
    Seminar: Networks, dynamic models and ML for data integration in the life sciences (Katharina Baum, Pauline Hiort, Pascal Iversen)
    Schedule: Fr 12:00-13:30 (Class starts on: 2024-07-26)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Comments

    Research seminar of the group Data Integration in the Life Sciences (DILiS). Also open for seminar participation in the Master's program, online participation possible. Please refer to the current schedule on the whiteboard!

    The seminar offers space for the discussion of advanced and integrative data analysis techniques, in particular presentations and discussion of ongoing or planned research projects, news from conferences, review and discussion of current literature and discussion of possible future teaching formats and content, and presentations, as well as final presentations on theses or project seminars. The seminar language is mostly English. Interested students are welcome to attend and drop in without obligation or present a topic of their own choice of interest to the working group as in a usual seminar. Please note: Individual dates may be canceled or postponed. Please contact me in case of questions (katharina.baum@fu-berlin.de)!

  • 19335804 PC-based Seminar
    Programming Lab (N.N.)
    Schedule: -
    Location: keine Angabe
    

    Comments

    Students work on many small practical learning tasks. They can choose these from a large set of candidate tasks in various topic areas, such as:

    • Programming languages
    • Selection and use of libraries
    • Databases and SQL
    • Automated tests
    • Debugging,
    • Working with existing code
    • Web development
    • Working with tools such as version management, package management, IDEs, testing tools etc..

    The material has enormously high relevance for building professional software development skills.
    Work is mostly done in pairs, to help with reflection and for overcoming roadblocks.

  • 19335901 Lecture
    Embedded Systems Architecture (Larissa Groth)
    Schedule: Mi 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-16)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    

    Comments

    Students learn the basic structure of microprocessor architectures for embedded systems including data formats, instruction formats, instruction sets and memory organization. They learn and practise the practical scope of interfaces and input/output systems and peripheral devices. They will learn about the properties of cyber physical systems, sensors, actuators and wireless sensor networks (WSN) and discuss their areas of application. They also learn how to connect and use field programmable gate arrays (FPGAs) and practise the application-related programming of embedded systems in C and Assembler. They also learn the basic structure of current operating systems for embedded systems, in particular real-time operating systems, real-time scheduling and real-time communication, and practise their implementation. Finally, aspects of the security of embedded systems including attack vectors, process isolation and trusted computing are discussed and evaluated.

  • 19335902 Practice seminar
    Embedded System Architecture Tutorials (Larissa Groth)
    Schedule: Mo 14:00-16:00 (Class starts on: 2024-10-14)
    Location: K 063 Hardwarepraktikum (Takustr. 9)
    
  • 19336311 Seminar
    Visualization for Artificial Intelligence Explainability (Georges Hattab)
    Schedule: Mi 10:00-12:00 (Class starts on: 2024-10-23)
    Location: A3/019 Seminarraum (Arnimallee 3-5)
    

    Comments

    As AI systems grow more powerful, there is an increasing need to make these complex "black box" models interpretable and explainable. This seminar explores how data visualization techniques can provide crucial insights into how AI models operate and arrive at their outputs. Cutting-edge methods like saliency maps, decision trees, and dimensionality reduction visualizations allow us to peer inside deep neural networks and understand what factors they are considering.

     

    The seminar also covers visualization literacy - effectively communicating AI explainability visualizations to different stakeholders. Case studies highlight best practices for visualizing model behavior, evaluating fairness, and instilling appropriate levels of trust. Attendees will gain an understanding of how visualization can demystify AI, foster transparency, and enable real-world deployment of these systems in high-stakes domains.

  • 19336717 Seminar / Undergraduate Course
    Graph-neural networks in the life sciences and beyond (Katharina Baum, Pauline Hiort, Pascal Iversen)
    Schedule: Di 12:00-14:00 (Class starts on: 2024-10-15)
    Location: A6/SR 009 Seminarraum (Arnimallee 6)
    

    Comments

    Complex data can often be naturally modeled as a graph. Graphs or networks describe the interaction between objects and are an effective tool to represent systems in many applications. Graph neural networks are neural networks that directly input graphs and have recently emerged as a powerful tool to analyze networks and to predict properties of nodes and connections.

    This seminar offers an in-depth exploration of Graph Neural Networks (GNNs) and their applications across various domains, with a particular emphasis on the life sciences and biomedicine. We will begin by discussing the fundamental concepts and architectures of GNNs, including graph convolutional networks (GCNs) and graph attention networks (GATs). Applications that are discussed include protein-protein interaction networks, drug discovery and personalized medicine. Students will read and present research papers and participate in critical discussions.

    The language of this seminar is planned to be English. The students are encouraged to present and discuss in English, but contributions in German are also possible.

  • 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.

  • 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)
    
  • 19337001 Lecture
    Mathematics for Computer Science Teachers (Max Willert)
    Schedule: Mo 16:00-18:00 (Class starts on: 2024-10-14)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Comments

    Qualification objectives: Students formulate³ statements formally using propositional and predicate logic. They analyze⁴ and simplify³ the logical structure of given statements and describe⁴ the logical structure of proofs. They name properties of different sets, relations and functions and justify⁴ these with the help of formal arguments. They can develop proofs for elementary statements using elementary proof techniques⁵ and determine the cardinality of sets using combinatorial techniques as well as probabilities of random events³.

    Contents: Students learn basic concepts of set theory, logic and combinatorics and practise their application. They work on sets, relations and functions in set theory. In the field of logic and Boolean algebra, they learn aspects of propositional logic and predicate logic. In the field of combinatorics, they learn about factorials and binomial coefficients. They also learn elementary proof techniques and basic aspects of discrete probability theory. Finally, formal languages are used as examples for modeling. Most of these concepts are practiced on calculation or proof problems.

    Suggested reading

    • Kenneth H. Rosen. Discrete Mathematics and its Applications, McGaw-Hill Education, 8. Auflage, 2018.
    • Gerald Teschl und Susanne Teschl. Mathematik für Informatiker - Band 1: Diskrete Mathematik und Lineare Algebra, Springer Vieweg, 4. Auflage, Berlin Heidelberg 2013.

  • 19337002 Practice seminar
    Mathematics for Computer Science Teachers (Exercises) (Max Willert)
    Schedule: Do 16:00-18:00 (Class starts on: 2024-10-17)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    
  • 19337211 Seminar
    Representation Learning (Georges Hattab)
    Schedule: Mi 14:00-16:00 (Class starts on: 2024-10-23)
    Location: A3/019 Seminarraum (Arnimallee 3-5)
    

    Comments

    While traditional feature engineering has been successful, modern machine learning increasingly relies on representation learning - automatically discovering informative features or representations from raw data. This seminar dives into advanced neural network-based approaches that learn dense vector representations capturing the underlying explanatory factors in complex, high-dimensional datasets.

     

    The seminar will cover techniques like autoencoders, variational autoencoders, and self-supervised contrastive learning methods that leverage unlabeled data to learn rich representations. You'll learn about properties of effective learned representations like preserving locality, handling sparse inputs, and disentangling underlying factors. Case studies demonstrate how representation learning enables breakthrough performance on tasks like image recognition and natural language understanding. You'll gain insights into interpreting these learned representations as well as their potential and limitations.