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Computer Science

Computer Science

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  • Fundamentals of Programming

    0086eA1.1
    • 19300001 Lecture
      Konzepte der Programmierung (Katharina Klost)
      Schedule: Mo 14:00-16:00, Mi 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-13)
      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 (Katharina Klost, Kristin Knorr)
      Schedule: Mi 14:00-16:00, Mi 16:00-18:00, Do 08:00-10:00, Do 12:00-14:00, Do 16:00-18:00, Fr 08:00-10:00, Fr 10:00-12:00, Fr 12:00-14:00, Fr 14:00-16:00 (Class starts on: 2025-10-15)
      Location: T9/049 Seminarraum (Takustr. 9)

      Comments

      Tutorien finden erst ab der 2. Vorlesungswoche statt

  • Database Systems

    0086eA1.11
    • 19301501 Lecture
      Database Systems (Katharina Baum)
      Schedule: Di 10:00-12:00, Di 12:00-13:00, Di 14:00-16:00, Do 10:00-12:00 (Class starts on: 2025-10-14)
      Location: T9/SR 005 Übungsraum (Takustr. 9)

      Additional information / Pre-requisites

      Requirements

      • ALP 1 - Functional Programming
      • ALP 2 - Object-oriented Programming
      • ALP 3 - Data structures and data abstractions
      • OR Informatik B

      Comments

      Content

      Database design with ERM/ERDD. Theoretical foundations of relational database systems: relational algebra, functional dependencies, normal forms. Relational database development: SQL data definitions, foreign keys and other integrity constraints, SQL as applicable language: essential language elements, embedding in programming language. Application programming; object-relational mapping. Security and protection concepts. Transaction subject, transactional guaranties, synchronization of multi user operations, fault tolerance features. Application and new developments: data warehousing, data mining, OLAP.

      Project: the topics are deepened in an implementation project for student groups.

      Suggested reading

      • Alfons Kemper, Andre Eickler: Datenbanksysteme - Eine Einführung, 5. Auflage, Oldenbourg 2004
      • R. Elmasri, S. Navathe: Grundlagen von Datenbanksystemen, Pearson Studium, 2005
    • 19301502 Practice seminar
      Practice seminar for Database systems (Pascal Iversen)
      Schedule: Mi 12:00-14:00 (Class starts on: 2025-10-15)
      Location: T9/049 Seminarraum (Takustr. 9)

  • Programming Lab

    0086eA1.12
    • 19335804 PC-based Seminar
      Programming Lab (Lutz Prechelt)
      Schedule: Mo 16:00-18:00, Di 16:00-18:00, Mi 16:00-18:00, Do 16:00-18:00, Fr 16:00-18:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-13)
      Location: T9/K48 Rechnerpoolraum (Takustr. 9)

      Additional information / Pre-requisites

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

      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.

  • Academic Work in Computer Science

    0086eA1.16
    • 19319701 Lecture
      Scientific Work/Research in Computer Science (Claudia Müller-Birn)
      Schedule: Di 16:00-18:00 (Class starts on: 2025-10-14)
      Location: T9/Gr. Hörsaal (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.
    • 19301710 Proseminar
      Undergraduate Seminar: Theoretical Computer Science (Mahmoud Elashmawi)
      Schedule: Di 10:00-12:00 (Class starts on: 2025-10-14)
      Location: T9/K40 Multimediaraum (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, we consider advanced topics from the theory of computability and of formal languates (in continuation of "Theory of Computation"); during the summer semester, we talk about algorithms (in continuation of "Algorithms, Data Structures, and Data Abstraction").

      Prerequisites

      two semesters of computer science, successful completion of "Theory of Computation"

      Suggested reading

      wird mit der Ankündigung bekannt gegeben
    • 19310817 Seminar / Undergraduate Course
      Seminar/Proseminar: Internet of Things & Security (Computer Systems & Telematics) (Emmanuel Baccelli)
      Schedule: Mi 10:00-12:00 (Class starts on: 2025-10-15)
      Location: T9/K40 Multimediaraum (Takustr. 9)

      Comments

      Seminar Technische Informatik on Internet of Things & Security

      NOTE WELL: This seminar is research-oriented, in english, and primarily aimed at Masters students. You will learn how to survey and present academic work in written and oral form. Down the line, it may prepare you for a thesis on the topic you survey during the seminar.

      WARNING: This seminar is demanding. The schedule is tight, and you will have to put substantial work into surveying related work (breadth coverage), studying a specific technique (depth coverage) and structuring the written and oral presentation of your survey (tending towards an acceptable academic research level).

      SYNOPSIS: In large part, the deep edge (aka the Internet of Things, or IoT) consists of distributed systems including low-end devices with very small memory capacity (a few kBytes) and limited energy consumption (1000 times less than a RaspberryPi). Deep edge capabilities promise a new world of applications, but also bring 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 low-power deep edge computing, Internet of Things and security, and write a report (IEEE LaTeX template, approx. 12 pages including figures and references, A4, double column, 1.5 spacing, 11-point font) discussing corresponding questions. At the end of the term, the participants present their results in the form of a short talk (15 minutes + 5 minutes Q&A) in a meeting, which will also include cross-reviewing of student's presentations. During the term, there will be deadlines for status reports, but no weekly meetings of the complete seminar group.

      Attendance is mandatory only for the introductory session, a mid-term presentation, and the final presentation at the end of the term.

      SCHEDULE

      Mid-October: introductory session (presence mandatory)
      After 1 week: topic selection
      After 4 weeks: preliminary presentation & 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 onscholar.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).
    • 19328217 Seminar / Undergraduate Course
      Seminar/Proseminar: New Trends in Information Systems (Agnès Voisard)
      Schedule: Mi 10:00-12:00 (Class starts on: 2025-10-15)
      Location: T9/053 Seminarraum (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.
    • 19329617 Seminar / Undergraduate Course
      Seminar/Proseminar: Telematics (Jochen Schiller)
      Schedule: Termine siehe LV-Details (Class starts on: 2026-02-09)
      Location: T9/049 Seminarraum (Takustr. 9)

      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. 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.

       

       
    • 19334617 Seminar / Undergraduate Course
      Seminar/Proseminar: Beyond LLMs: Recent Breakthroughs in AI (Tim Landgraf)
      Schedule: Mi 10:00-12:00 (Class starts on: 2025-10-15)
      Location: T9/049 Seminarraum (Takustr. 9)

  • Discrete Structures in Computer Science

    0086eA1.2
    • 19300901 Lecture
      Discrete Structures for Computer Science (Max Willert)
      Schedule: Di 14:00-16:00, Do 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-14)
      Location: Gr. Hörsaal (Raum B.001) (Arnimallee 22)

      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 (Max Willert)
      Schedule: Mo 08:00-10:00, Mo 10:00-12:00, Mo 16:00-18:00, Di 08:00-10:00, Di 10:00-12:00, Di 12:00-14:00, Di 16:00-18:00 (Class starts on: 2025-10-13)
      Location: T9/053 Seminarraum (Takustr. 9)

  • Impacts of Computer Science

    0086eA1.3
    • 19301301 Lecture
      Consequences of Computer Science (Lutz Prechelt)
      Schedule: Mo 12:00-14:00 (Class starts on: 2025-10-13)
      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 (Linus Ververs)
      Schedule: Mo 10:00-12:00, Di 10:00-12:00, Di 12:00-14:00, Di 16:00-18:00, Mi 08:00-10:00, Mi 10:00-12:00, Mi 14:00-16:00, Mi 16:00-18:00, Do 16:00-18:00 (Class starts on: 2025-10-13)
      Location: T9/051 Seminarraum (Takustr. 9)

      Comments

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

  • Computer Architecture

    0086eA1.6
    • 19300601 Lecture
      Computer Architecture (Larissa Groth)
      Schedule: Di 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-14)
      Location: , Hs 1a Hörsaal, T9/Gr. Hörsaal

      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, Marius Max Wawerek)
      Schedule: Mo 12:00-14:00, Mo 14:00-16:00, Mi 12:00-14:00, Mi 14:00-16:00, Do 14:00-16:00, Do 16:00-18:00, Fr 12:00-14:00, Fr 14:00-16:00 (Class starts on: 2025-10-13)
      Location: T9/K38 Rechnerpoolraum (Takustr. 9)

  • Fundamentals of Theoretical Computer Science

    0086eA1.7
    • 19301201 Lecture
      Foundations of Theoretical Computer Science (Günther Rothe)
      Schedule: Mo 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-20)
      Location: Hs 1b Hörsaal (Habelschwerdter Allee 45)

      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 (Günther Rothe)
      Schedule: Mo 12:00-14:00, Di 16:00-18:00, Mi 08:00-10:00, Mi 14:00-16:00, Mi 16:00-18:00, Do 08:00-10:00, Fr 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-13)
      Location: A7/SR 031 (Arnimallee 7)

  • Concurrent, Parallel, and Distributed Programming

    0086eA1.8
    • 19322101 Lecture
      Concurrent, Parallel, and Distributed Programming (Claudia Müller-Birn, Barry Linnert)
      Schedule: Mi 10:00-12:00, Do 12:00-14:00 (Class starts on: 2025-10-15)
      Location: T9/Gr. Hörsaal (Takustr. 9)

      Comments

      Website: https://www.mi.fu-berlin.de/w/SE/VorlesungNichtseq_Vert_Prg2025

       

      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

      Literature:

      • 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, Di 10:00-12:00, Do 10:00-12:00, Do 14:00-16:00, Fr 12:00-14:00, Fr 16:00-18:00 (Class starts on: 2025-10-14)
      Location: T9/SR 006 Seminarraum (Takustr. 9)

  • Analysis for Computer Scientists

    0086eA1.9
    • 19301101 Lecture
      Analysis for Computer Science and Bioinformatics (Klaus Kriegel)
      Schedule: Di 14:00-16:00, Fr 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-10-14)
      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: Mo 12:00-14:00, Mo 16:00-18:00, Di 16:00-18:00, Mi 12:00-14:00, Mi 16:00-18:00, Do 08:00-10:00, Do 10:00-12:00, Do 16:00-18:00, Fr 08:00-10:00, Fr 14:00-16:00 (Class starts on: 2025-10-13)
      Location: T9/046 Seminarraum (Takustr. 9)

  • Current Topics in Computer Science

    0086eB1.12

  • Architecture of Embedded Systems

    0086eB1.2
    • 19335901 Lecture
      Embedded Systems Architecture (Larissa Groth)
      Schedule: Fr 14:00-16:00 (Class starts on: 2025-10-24)
      Location: T9/SR 005 Übungsraum (Takustr. 9)

      Additional information / Pre-requisites

      Important information about the schedule:
      Architecture of Embedded Systems will exceptionally be offered this winter semester with the following dates:

      • Lecture: Fridays, 2–4 p.m., Takustraße 9, Room K40

      • Exercise Group A: Tuesdays, 2–4 p.m., Takustraße 9, Room K63

      • Exercise Group B: Wednesdays, 12–2 p.m., Takustraße 9, Room K63

      You must choose one of the exercise sessions.

      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: -
      Location: keine Angabe

  • Data Visualization

    0086eB1.3
    • 19328301 Lecture
      Data Visualization (Claudia Müller-Birn)
      Schedule: Di 12:00-14:00 (Class starts on: 2025-10-14)
      Location: T9/SR 005 Übungsraum (Takustr. 9)

      Additional information / Pre-requisites

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

      Comments

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

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

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

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

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

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

      Suggested reading

      Textbook

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

      Additional Literature

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

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

      Spence, Robert: Information Visualization: Design for Interaction. Pearson. 2007.
    • 19328302 Practice seminar
      Data Visualization (Malte Heiser)
      Schedule: Do 08:00-10:00, Do 10:00-12:00 (Class starts on: 2025-10-16)
      Location: T9/SR 005 Übungsraum (Takustr. 9)

  • Machine Learning

    0086eB1.7
    • 19336201 Lecture
      Machine Learning (Gerhard Wunder)
      Schedule: Mi 12:00-14:00 (Class starts on: 2025-10-15)
      Location: T9/SR 006 Seminarraum (Takustr. 9)

      Comments

      Qualifikationsziele: Die Studierenden lernen Formen der Datenrepräsentation und deren Visualisierung, können Abhängigkeiten aufzeigen und wenden Verfahren für Dimensionsreduktion und Datenvorverarbeitung an. Sie lernen die Grundbegriffe und Prinzipien des maschinellen Lernens, können Zielkriterien formulieren, benennen Eigenschaften von Optimierungsproblemen und können algorithmische Ansätze zur Lösung umsetzen. Sie können unterschiedlichste Lernverfahren zur Regression, Klassifikation und Entscheidungsfindung einordnen und umsetzen. Sie lernen die Grundstrukturen und Architekturen von neuronalen Netzen und deren vielfältige Einsatzgebiete. Sie können algorithmisch Lösungen für eine gegebene Problemstellung umsetzen und evaluieren.

      Inhalte: Die Studierenden erlernen die Grundlagen des maschinellen Lernens, der Lerntheorie, der Generalisierung und PAC. Sie erarbeiten ebenfalls die Grundlagen der konvexen Optimierung (z. B. Subgradient Methode), des Stochastischen Gradientenabstieg, der Regularisierung und Konvergenz. Sie üben Verfahren des Supervised Learning (z. B. Linear Regression, SVM, Kernel-Trick), des Unsupervised Learning (z. B. Clustering, Decision Trees, Matrix Decomposition, wie PCA) und des Dictionary Learning. Des Weiteren erlernen Studierende die Grundlagen der Künstliche Neuronale Netze (KNN), indem mögliche Architekturen und das Konzept der Backpropagation erarbeitet werden. Darüber hinaus setzen sich Studierende mit den Aspekten der Evaluierung (Crossvalidation, Hyper-Parameter-Tuning usw.) auseinande
    • 19336202 Practice seminar
      Übung zu Maschinelles Lernen (Gerhard Wunder)
      Schedule: Mo 14:00-16:00 (Class starts on: 2025-10-20)
      Location: , T9/SR 006 Seminarraum

  • Analysis II

    0084dA1.2
    • 19211601 Lecture
      Analysis II (Pavle Blagojevic)
      Schedule: Di 10:00-12:00, Do 10:00-12:00 (Class starts on: 2025-10-14)
      Location: A3/Hs 001 Hörsaal (Arnimallee 3-5)

      Comments

      Content

      1. Additions to Analysis I. Non-authentic integrals
      2. Uniform convergence of function sequences. Power series. Sentence of Taylor.
      3. Elements of topology. Standardized and metric spaces. Open quantities. Convergence. Completed quantities. Consistency. Compactness
      4. Differential calculus of several variables. Partial, total and continuous differentiability. Block via the inverse function. Block of implicit functions.
      5. Iterated integrals.
      6. Ordinary differential equations. Basic terms, elementary solvable differential equations, existential and unambiguous results for systems.

      Suggested reading

      • O. Forster: Analysis 1 und 2. Vieweg/Springer.
      • Königsberger, K: Analysis 1,2, Springer.
      • E. Behrends: Analysis Band 1 und 2, Vieweg/Springer.
      • H. Heuser: Lehrbuch der Analysis 1 und 2, Teubner/Springer.

  • Linear Algebra II

    0084dA1.5
    • 19211701 Lecture
      Linear Algebra II (Marcus Weber)
      Schedule: Mo 08:00-10:00, Do 14:00-16:00 (Class starts on: 2025-10-16)
      Location: A3/Hs 001 Hörsaal (Arnimallee 3-5)

      Additional information / Pre-requisites

      See http://page.mi.fu-berlin.de/werner99/.

      Comments

      Contents:

      • Determinants
      • Eigenvalues and eigenvectors: diagonalizability, trigonalizability, set of Cayley-Hamilton, Jordanian normal form
      • Bilinear forms
      • Vectorräume with scalar product: Euclidean, unitary vectorräume, orthogonal projection, isometries, self-adjusted images, Gram-Schmidt orthonormalization methods, major axis transformation

      Prerequisites:
      Linear Algebra I
      Literature:

      Will be mentioned in the lecture.
    • 19211702 Practice seminar
      Practice seminar for Linear Algebra II (Marcus Weber)
      Schedule: Di 08:00-10:00, Di 14:00-16:00, Mi 12:00-14:00, Do 16:00-18:00, Fr 08:00-10:00 (Class starts on: 2025-10-14)
      Location: A3/019 Seminarraum (Arnimallee 3-5)

  • Computer-Oriented Mathematics I

    0084dA1.6
    • 19200501 Lecture
      Computerorientated Mathematics I (5 LP) (Claudia Schillings)
      Schedule: Fr 12:00-14:00 (Class starts on: 2025-10-17)
      Location: T9/Gr. Hörsaal (Takustr. 9)

      Comments

      Contents:
      Computers play an important role in (almost) all situations in life today. Computer-oriented mathematics provides basic knowledge in dealing with computers for solving mathematical problems and an introduction to algorithmic thinking. At the same time, typical mathematical software such as Matlab and Mathematica will be introduced. The motivation for the questions under consideration is provided by simple application examples from the aforementioned areas. The content of the first part includes fundamental terms of numerical calculation: number representation and rounding errors, condition, efficiency and stability.

      Homepage: All current information on lectures and lectures

      Suggested reading

      Literatur: R. Kornhuber, C. Schuette, A. Fest: Mit Zahlen Rechnen (Skript zur Vorlesung)
    • 19200502 Practice seminar
      Practice seminar for Computerorientated Mathematics I (5 LP) (N.N.)
      Schedule: Mo 12:00-14:00, Mo 14:00-16:00, Di 08:00-10:00, Di 16:00-18:00, Mi 10:00-12:00, Do 14:00-16:00, Fr 08:00-10:00 (Class starts on: 2025-10-13)
      Location: A6/SR 031 Seminarraum (Arnimallee 6)

  • Numerical Mathematics I

    0084dA1.9
    • 19212001 Lecture
      Numerics I (Volker John)
      Schedule: Mo 10:00-12:00, Mi 10:00-12:00 (Class starts on: 2025-10-13)
      Location: A7/SR 031 (Arnimallee 7)

      Comments

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

      Suggested reading

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

      Aus dem FU-Netz auch online verfügbar.

      Es wird ein Vorlesungsskript geben.

      Link
    • 19212002 Practice seminar
      Practice seminar for Numerics I (N.N.)
      Schedule: Di 08:00-10:00, Di 10:00-12:00, Fr 08:00-10:00 (Class starts on: 2025-10-14)
      Location: A3/019 Seminarraum (Arnimallee 3-5)

  • Academic Work in Mathematics

    0084dB1.1
    • 19208111 Seminar
      Masterseminar Stochastics "Mathematical Reinforcement Learning for AI" (Guilherme de Lima Feltes, Dave Jacobi, Nicolas Perkowski)
      Schedule: Do 16:00-18:00 (Class starts on: 2025-10-16)
      Location: A7/SR 140 Seminarraum (Hinterhaus) (Arnimallee 7)

      Additional information / Pre-requisites

      Prerequisites: Stochastics I and II. Desirable: Stochastics III.
      Target Group: BMS Students, Master students of Mathematics and advanced Bachelor students of Mathematics.

      Comments

      Content: The seminar covers advanced topics of stochastics.

      Detailed Information can be found on the Homepage of the seminar.

      Reinforcement learning lies at the core of many state-of-the-art artificial intelligence algorithms, enabling agents to solve complex optimal control tasks in robotics, finance, physical AI, drug discovery, computer games and many other applications.
      This seminar offers a rigorous treatment of reinforcement learning, focusing on the mathematical principles that make reinforcement learning algorithms work. We will develop a mathematically sound understanding of Markov decision processes, value function based methods and their connections to stochastic optimal control, policy gradient methods, emphasizing convergence properties of classical reinforcement learning algorithms through stochastic approximation and stochastic gradient descent. We will also explore continuous time reinforcement learning in the framework of stochastic differential equations.
      The seminar aims to provide a rigorous foundational perspective for students interested in current research related to reinforcement learning and artificial intelligence. Participants should have a strong background in mathematics specifically in probability theory.

      Suggested reading

      Literatur wird in der Vorbesprechung bekanntgegeben.

      Literature will be announced in the preliminary discussion
    • 19212211 Seminar
      Seminar on topic in Geometric Analysis and Differential Geometry (Elena Mäder-Baumdicker)
      Schedule: Mi 15.10. 12:00-14:00, Mi 05.11. 12:00-14:00 (Class starts on: 2025-10-15)
      Location: A3/SR 115 (Arnimallee 3-5)

      Additional information / Pre-requisites

      Ana I bis III, lineare Algebra I und II sowie mindestens einer der beiden Vorlesungen Differentialgeometrie I oder Differentialgleichungen I.

      Comments

      This seminar is intended for Bachelor's and Master's students with an interest in topics related to Geometric Analysis and Differential Geometry. Each semester, the seminar focuses on a different theme — examples include geometric variational problems, geometric flows, and geometric measure theory.

      In the first meeting of the semester, students can express their interest in participating. In the second meeting, each participant selects a topic from a curated list. The presentations themselves will take place during a dedicated seminar week at the end of the term.

       
    • 19226511 Seminar
      Seminar Multiscale Methods in Molecular Simulations (Luigi Delle Site)
      Schedule: Fr 12:00-14:00 (Class starts on: 2025-10-17)
      Location: Seminarraum in der Arnimallee 9

      Additional information / Pre-requisites

      Audience: At least 6th semester with a background in statistical and quantum mechanics, Master students and PhD students (even postdocs) are welcome.

      Comments

      Content: The seminar will concern the discussion of state-of-art techniques in molecular simulation which allow for a simulation of several space (especially) and time scale within one computational approach.

      The discussion will concerns both, specific computational coding and conceptual developments.

      Suggested reading

      Related Basic Literature:

      (1) M.Praprotnik, L.Delle Site and K.Kremer, Ann.Rev.Phys.Chem.59, 545-571 (2008)

      (2) C.Peter, L.Delle Site and K.Kremer, Soft Matter 4, 859-869 (2008).

      (3) M.Praprotnik and L.Delle Site, in "Biomolecular Simulations: Methods and Protocols" L.Monticelli and E.Salonen Eds. Vol.924, 567-583 (2012) Methods Mol. Biol. Springer-Science
    • 19240317 Seminar / Undergraduate Course
      Advancing mathematics with AI (Georg Loho)
      Schedule: Di 14:00-16:00 (Class starts on: 2025-10-14)
      Location: A3/SR 120 (Arnimallee 3-5)

      Comments

      The course will probably be held in German. 
    • 19247111 Seminar
      Ordinary Differential Equations (Marita Thomas)
      Schedule: Di 16:00-18:00 (Class starts on: 2025-10-14)
      Location: A6/SR 009 Seminarraum (Arnimallee 6)

      Comments

      Ordinary differential equations arise in many applications from physics, chemistry, biology or economics. This seminar extends the topics that were covered in the Analysis III course, e.g., eigenvalue problems and stability theory will be addressed. 

  • Special topics in Mathematics

    0084dB2.11
    • 19202001 Lecture
      Discrete Geometrie I (Christian Haase)
      Schedule: Di 10:00-12:00, Mi 12:00-14:00 (Class starts on: 2025-10-14)
      Location: A3/SR 120 (Arnimallee 3-5)

      Additional information / Pre-requisites

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

      Comments

      Physical presence in the exercises on Wednesdays is mandatory.

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

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

       

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

       

       

       

       

       

       

       

       

       

      Suggested reading

      • G.M. Ziegler "Lectures in Polytopes"
      • J. Matousek "Lectures on Discrete Geometry"
      • Further literature will be announced in class.
    • 19202002 Practice seminar
      Practice seminar for Discrete Geometrie I (Sofia Garzón Mora, Christian Haase)
      Schedule: Mi 14:00-16:00 (Class starts on: 2025-10-15)
      Location: A6/SR 031 Seminarraum (Arnimallee 6)

  • Special topics in Pure Mathematics

    0084dB2.12
    • 19236101 Lecture
      Mathematisches Panorama (Anina Mischau, Sarah Wolf)
      Schedule: Mi 12:00-14:00 (Class starts on: 2025-10-15)
      Location: T9/SR 005 Übungsraum (Takustr. 9)

      Comments

      This is for a course in German - Short explanation in English:

      Mathematical Panorama is a two-hour overview course for First-Semester students of Mathematics (in particular, but not only, for teacher students) that presents the wide field of modern Mathematics - its history, its topics, its problems, its methods, some basic concepts, applications, etc.

       

      Suggested reading

      • Günter M. Ziegler und Andreas Loos: Panorama der Mathematik, Springer-Spektrum 2018, in Vorbereitung (wird in Auszügen zur Verfügung gestellt)
      • Hans Wußing, 6000 Jahre Mathematik: Eine kulturgeschichtliche Zeitreise, Springer 2009
        • Band 1: Von den Anfängen bis Leibniz und Newton
        • Band 2: Von Euler bis zur Gegenwart
      • Heinz-Wilhelm Alten et al., 4000 Jahre Algebra, Springer 2008
      • Christoph J. Scriba, 5000 Jahre Geometrie, Springer 2009
      • Heinz Niels Jahnke, Geschichte der Analysis: Texte zur Didaktik der Mathematik, Spektrum 1999
      • Richard Courant und Herbert Robbins, What is Mathematics?, Oxford UP 1941 (deutsch: Springer 2010)
      • Phillip J. Davis, Reuben Hersh, The Mathematical Experience, Mariner Books 1999
    • 19236102 Practice seminar
      Übung zu: Mathematisches Panorama (Anina Mischau)
      Schedule: Mo 14:00-16:00, Do 14:00-16:00, Do 16:00-18:00, Fr 12:00-14:00 (Class starts on: 2025-10-20)
      Location: A6/SR 007/008 Seminarraum (Arnimallee 6)

  • Functional Analysis

    0084dB2.2
    • 19201901 Lecture
      Functional Analysis (Dirk Werner)
      Schedule: Di 10:00-12:00, Do 10:00-12:00 (Class starts on: 2025-10-14)
      Location: A3/019 Seminarraum (Arnimallee 3-5)

      Comments

      Content:
      Functional analysis is the branch of mathematics dealing with the study of normed (or general topological) vector spaces and continuous mappings between them. Thus, analysis, topology and algebra are linked.
      The course deals with Banach and Hilbert spaces, linear operators and functionals as well as spectral theory of compact operators.

      Target group: Students from the 3rd/4th semester on.

      Requirements: Good command of the material of the courses Analysis I/II and Linear Algebra I/II.

      Suggested reading

      Literatur:

      • Dirk Werner: Funktionalanalysis, 8. Auflage, Springer-Verlag 2018
    • 19201902 Practice seminar
      Tutorial: Functional Analysis (Piotr Pawel Wozniak)
      Schedule: Do 12:00-14:00 (Class starts on: 2025-10-16)
      Location: KöLu24-26/SR 006 Neuro/Mathe (Königin-Luise-Str. 24 / 26)

      Comments

      Inhalt:
      Die Funktionalanalysis ist der Zweig der Mathematik, der sich mit der Untersuchung von normierten (oder allgemeiner topologischen) Vektorräumen und stetigen Abbildungen zwischen ihnen befasst. Hierbei werden Analysis, Topologie und Algebra verknüpft.
      Die Vorlesung behandelt Banach- und Hilberträume, lineare Operatoren und Funktionale sowie Spektraltheorie kompakter Operatoren.

      Zielgruppe: Studierende vom 4. Semester an.

      Voraussetzungen: Sicheres Beherrschen des Stoffs der Vorlesungen Analysis I/II und Lineare Algebra I/II.

      Literatur:

       

      • Dirk Werner: Funktionalanalysis, 6. Auflage, Springer-Verlag 2007, ISBN 978-3-540-72533-6
      • Hans Wilhelm Alt: Lineare Funktionalanalysis : eine anwendungsorientierte Einführung. 5. Auflage. Springer-Verlag, 2006, ISBN 3-540-34186-2
      • Harro Heuser: Funktionalanalysis: Theorie und Anwendung. 3. Auflage. Teubner-Verlag, 1992, ISBN 3-519-22206-X

       

  • Probability and Statistics II

    0084dB2.4
    • 19212901 Lecture
      Stochastics II (Felix Höfling)
      Schedule: Di 12:00-14:00, Do 08:00-10:00 (Class starts on: 2025-10-14)
      Location: A3/Hs 001 Hörsaal (Arnimallee 3-5)

      Additional information / Pre-requisites

      Prerequisite: Stochastics I  and  Analysis I — III.

      Comments

      Contents:

      • Basics: conditional expectation, characteristic function, convergence types, uniform integrability;
      • Construction of stochastic processes and examples: Gaussian processes, Lévy processes, Brownian motion;
      • martingales in discrete time: convergence, stopping theorems, inequalities;
      • Markov chains in discrete and continuous time: recurrence and transience, invariant measures.

      Suggested reading

      • Klenke: Wahrscheinlichkeitstheorie
      • Durrett: Probability. Theory and Examples.

      Weitere Literatur wird im Lauf der Vorlesung bekannt gegeben.
      Further literature will be given during the lecture.
    • 19212902 Practice seminar
      Practice seminar for Stochastics II (Felix Höfling)
      Schedule: Di 14:00-16:00 (Class starts on: 2025-10-14)
      Location: A6/SR 031 Seminarraum (Arnimallee 6)

      Comments

      Inhalt

       

       

      • This course is the sequel of the course of Stochastics I. The main objective is to go beyond the first principles in probability theory by introducing the general language of measure theory, and the application of this framework in a wide variety of probabilistic scenarios.
        More precisely, the course will cover the following aspects of probability theory:
      • Measure theory and the Lebesgue integral
      • Convergence of random variables and 0-1 laws
      • Generating functions: branching processes and characteristic functions
      • Markov chains
      • Introduction to martingales

       

       

  • Algebra and Number Theroy

    0084dB2.5
    • 19200701 Lecture
      Algebra and Theory of Numbers (Alexander Schmitt)
      Schedule: Mo 08:00-10:00, Mi 08:00-10:00 (Class starts on: 2025-10-15)
      Location: T9/Gr. Hörsaal (Takustr. 9)

      Comments

      Subject matter:
      Selected topics from:

          Divisibility into rings (especially Z- and polynomial rings); residual classes and congruencies; modules and ideals
          Euclidean, principal ideal and factorial rings
          The quadratic law of reciprocity
          Primality tests and cryptography
          The structure of abel groups (or modules about main ideal rings)
          Symmetric function set
          Body extensions, Galois correspondence; constructions with compasses and rulers
          Non-Label groups (set of Lagrange, normal dividers, dissolvability, sylow groups)
    • 19200702 Practice seminar
      Practice seminar for Algebra and Theory of Numbers (Alexander Schmitt)
      Schedule: Mi 14:00-16:00, Do 14:00-16:00 (Class starts on: 2025-10-15)
      Location: A6/SR 025/026 Seminarraum (Arnimallee 6)

  • Discrete Mathematics I

    0084dB3.2
    • 19202001 Lecture
      Discrete Geometrie I (Christian Haase)
      Schedule: Di 10:00-12:00, Mi 12:00-14:00 (Class starts on: 2025-10-14)
      Location: A3/SR 120 (Arnimallee 3-5)

      Additional information / Pre-requisites

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

      Comments

      Physical presence in the exercises on Wednesdays is mandatory.

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

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

       

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

       

       

       

       

       

       

       

       

       

      Suggested reading

      • G.M. Ziegler "Lectures in Polytopes"
      • J. Matousek "Lectures on Discrete Geometry"
      • Further literature will be announced in class.
    • 19202002 Practice seminar
      Practice seminar for Discrete Geometrie I (Sofia Garzón Mora, Christian Haase)
      Schedule: Mi 14:00-16:00 (Class starts on: 2025-10-15)
      Location: A6/SR 031 Seminarraum (Arnimallee 6)

  • Numerical Mathematics II

    0084dB3.4
    • 19202101 Lecture
      Basic Module: Numeric II (Robert Gruhlke)
      Schedule: Mo 12:00-14:00, Mi 12:00-14:00 (Class starts on: 2025-10-15)
      Location: A3/Hs 001 Hörsaal (Arnimallee 3-5)

      Comments

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

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

      Prerequisites: Basics of calculus (Analysis I, II) linear algebra (Lineare Algebra I, II) and numerical analysis (Numerik I)
    • 19202102 Practice seminar
      Practice seminar for Basic Module: Numeric II (André-Alexander Zepernick)
      Schedule: Mi 10:00-12:00, Fr 08:00-10:00 (Class starts on: 2025-10-15)
      Location: A6/SR 025/026 Seminarraum (Arnimallee 6)

  • Differential Geometry I

    0084dB3.5
    • 19202601 Lecture
      Differential Geometry I (Konrad Polthier)
      Schedule: Mo 10:00-12:00, Mi 10:00-12:00 (Class starts on: 2025-10-15)
      Location: KöLu24-26/SR 006 Neuro/Mathe (Königin-Luise-Str. 24 / 26)

      Additional information / Pre-requisites

      For further information, see Lecture Homepage.

      Comments

      Topics of the lecture will be:

      • curves and surfaces in Euclidean space,
      • metrics and (Riemannian) manifolds,
      • surface tension, notions of curvature,
      • vector fields, tensors, covariant derivative
      • geodesic curves, exponential map,
      • Gauß-Bonnet theorem, topology,
      • connection to discrete differential geometry.

      This course is a BMS course and will be held in English on request.

      Prerequisits:

      Analysis I, II, III and Linear Algebra I, II

       

       

      Suggested reading

      Literature

      • W. Kühnel: Differentialgeometrie:Kurven - Flächen - Mannigfaltigkeiten, Springer, 2012
      • M. P. do Carmo, Differential Geometry of Curves and Surfaces, Prentice Hall
      • J.-H. Eschenburg, J. Jost: Differentialgeometrie und Minimalflächen, Springer, 2014
      • C. Bär: Elementare Differentialgeometrie, de Gruyter, 2001
    • 19202602 Practice seminar
      Practice seminar for Differential Geometry I (Tillmann Kleiner, Konrad Polthier)
      Schedule: Mo 08:00-10:00, Mi 08:00-10:00 (Class starts on: 2025-10-15)
      Location: A6/SR 031 Seminarraum (Arnimallee 6)

  • Modules w/o courses in this semester

    32 Modules
    • Operating and Communication Systems 0086eA1.10
    • Statistics for Students of Computer Science 0086eA1.13
    • Information Security 0086eA1.14
    • Software Technology 0086eA1.15
    • Algorithms and Data Structures 0086eA1.4
    • Linear Algebra for Computer Scientists 0086eA1.5
    • Applied Biometrics 0086eB1.1
    • Fundamentals of Data Privacy and Data Protection Law 0086eB1.10
    • Specialization: Theoretical Computer Science 0086eB1.11
    • Advanced Topics in Computer Science 0086eB1.13
    • Research Lab 0086eB1.4
    • Functional Programming 0086eB1.5
    • Information Theory 0086eB1.6
    • Man-Computer Interaction 0086eB1.8
    • Practices in Professional Software Development 0086eB1.9
    • Computer-Oriented Mathematics II 0084dA1.7
    • Probability and Statistics I 0084dA1.8
    • Higher Analysis 0084dB2.1
    • Current Topics in Mathematics 0084dB2.10
    • Special topics in Applied Mathematics 0084dB2.13
    • Complex Analysis 0084dB2.3
    • Elementary Geometry 0084dB2.6
    • Geometry 0084dB2.7
    • Mathematical Project 0084dB2.9
    • Differential Equations I 0084dB3.1
    • Algebra I 0084dB3.3
    • Topology I 0084dB3.6
    • Visualization 0084dB3.8.
    • Applied Modules: All Other Subjects 0086eC2.1
    • Applied Modules: All Other Subjects 0086eC2.2
    • Applied Modules: All Other Subjects 0086eC2.3
    • Oral Presentation of Bachelor's Thesis 0086eE1.2