Contents: 

Introduction to Functional Programming (Haskell): 

• Syntax (Backus-Naur Form) 
• primitive data types, lists, tuples, strings 
• • expressions, function definitions, recursion and iteration  evaluation strategies of functional programs
  • higher-order functions
  • polymorphism 
  • type system and verification 
• Algebraic and abstract data types 
• input, output and Monads
• searching and sorting algorithms 

Introduction of computability: 

• Lambda calculus 
• Primitive Recursion 
• μ-Recursion 

Proofs of program properties: 

• Term Rewriting 
• Structural induction 
• Termination 

Implementation and programming technique: 

• Modular program design

• Simon Thompson: Haskell: The Craft of Functional Programming, 2nd Edition, Addison-Wesley, 1999
• Graham Hutton: Programming in Haskell, Cambridge University Press, 2007
• Bird, R./Wadler, Ph.: Einführung in Funktionale Programmierung, Hanser Verlag, 1982
• Hans Hermes: Aufzählbarkeit, Entscheidbarkeit, Berechenbarkeit, Springer-Verlag 1978

Tutorien finden erst ab der 2. Vorlesungswoche statt

• Analysis of sorting algorithms: Mergesort, Quicksort, etc.
• ADTs priority queue and dictionary and corresponding data structures: heaps, hashing, binary search trees, B-trees, etc. 
• Graph algorithms: breadth first search and depth first search, topolocigal sorting, minimum spanning trees, shortest paths.
• Analysis on Strings.
• Memory-management.
• Algorithm design: divide-and-conquer, greedy algorithms, dynamic programming.
• Mathematical analysis of algorithms: running time, space.

• P. Morin: Open Data Structures, an open content textboox.
• T. H. Cormen, C. Leiserson, R. Rivest, C. Stein: Introduction to Algorithms, MIT Press, 2009.
• R. Sedgewick: Algorithms in Java (Part 1–5), Addison-Wesley, 2003.
• G. Saake, S. Sattler: Algorithmen und Datenstrukturen, dpunkt.verlag, 2013.
• M. Dietzfelbinger, K. Mehlhorn, P. Sanders. Algorithmen und Datenstrukturen: Die Grundwerkzeuge, Springer, 2014.
• M.T. Goodrich, R. Tamassia: Data Structures and Algorithms in Java, Wiley, 2014.

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.

• 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.

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.

• Stallings, W., & Paul, G. K.: Operating systems: internals and design principles (Vol. 9). New York: Pearson, 2012
• A.S. Tanenbaum: Modern Operating Systems, 2nd Ed. Prentice-Hall, 2001
• A. Silberschatz et al.: Operating Systems Concepts with Java, 6th Ed. Wiley, 2004

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

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

The main focus of the internship is the following:

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

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

See documents on the website - only from the FB network or via VPN website

Group A, Wednesday, 12-16 h Takustraße 9, Room K63 Group B, Thursday, 12-16 h Takustraße 9, Room K63

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.

• 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

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

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

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

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

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

Wechselnd, aufbauend auf der Vorlesung TI II: Rechnerarchitektur

Wird mit der Ankündigung bekannt gegeben.

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"

wird mit der Ankündigung bekannt gegeben

Technological impact assessment intends to make transparent how technology develops in social surroundings and which chances and risks are connected with its use.

Technological impact assessment

• analyses the impact of technology on society, environment, health, politics, economy
• focuses on potential intended as well as non-intended consequences
• tries to create options of acting and shaping future development

Within the lecture students will conduct an exemplary technological impact assessment process themselves.

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.

je nach Anwendungsgebiet

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.

Wird bekannt gegeben. / To be announced.

Target group

Students in the Master's or Bachelor's programme

Prerequisites

Good programming skills, introduction to database systems.

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

The project topic in the winter term 2021/22 is: Development of a semantic AI demonstrator to dect online hate speech.

Corporate Semantic Web

Corporate Semantic Web

Further information can be found on the course website

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.

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.

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

www.interdisciplinary-laboratory.hu-berlin.de

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 can play one or both of the following primary roles:

• Product owner. In this role, a student defines, prioritizes, communicates, and reviews requirements. The total effort adds up to a maximum of 5 ECTS.
• Software developer. In this role, a student estimates their effort for requirements and implements them.

A student can be a product owner, or a software developer, or both, depending on the ECTS afforded by the module (this course is available through many different modules).

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).
 

The schedule as well as further information about the course can be viewed via the following Google Spreadsheet: https://amos.uni1.de - here you will also find the registration link for the course.

http://goo.gl/5Wqnr7

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

Motivation

Since 1997, Berlin has had a three-stage popular participation procedure for the implementation of referendum petitions and referendums. Popular participation procedures belong to the group of direct democratic procedures and allow eligible voters to initiate votes on substantive issues outside of elections. This gives them the opportunity to exert direct political influence and address issues that may not have received sufficient attention in day-to-day politics.

Popular participation procedures are therefore of great importance for exercising the democratic will of eligible voters.

In the course of the almost 25 years long history of Berlin's popular participation procedures, a number of challenges have become apparent which, if overcome, could trigger democracy-strengthening potential.

One such challenge is the lack of transparency about all ongoing and previously conducted popular participation procedures. Currently, it is only possible to find details about the completed procedures (result, duration, number of signatures, ...) with enormous effort. The situation is similar for current procedures. There is no central point of contact where an overview of the current proceedings can be retrieved. Rather, one is dependent on the initiators' willingness to provide information, which is often neither complete nor up-to-date. Furthermore, there is no uniform presentation, since each initiator has a different focus on the presentation of information.

This situation is problematic for interested parties, regardless of whether they are initiators or eligible voters. Those entitled to vote, for example, cannot find out with reasonable effort which procedures are currently being carried out, which has a direct impact on possible participation. In turn, the initiators have to invest a lot of effort in achieving sufficient visibility. At the same time, they do not have a comprehensive understanding of what data and information might be of interest and in what form.

Other groups, such as the media, would benefit equally from comprehensive transparency.

The motivation for this software project is therefore the effective optimization of the popular participation procedures of the state of Berlin by bringing about more transparency. Therefore, a solution is needed that at least makes the status of current and future procedures visible. The most important criteria here are completeness and central as well as uniform availability of the data.

Further information on direct democracy and popular participation procedures can be found here:

https://www.berlin.de/sen/inneres/buerger-und-staat/wahlen-und-abstimmungen/volksinitiative-volksbegehren-volksentscheid/volksbegehren-und-volksentscheid/artikel.24015.php

https://www.berlin.de/politische-bildung/politikportal/politik-in-berlin/wahlen-und-direkte-demokratie/direkte-demokratie/

https://bb.mehr-demokratie.de/berlin/berlin-volksbegehren/berlin-land-uebersicht/

https://de.wikipedia.org/wiki/Volksgesetzgebung_in_Berlin

Contents

The subject of this project is the development of a web application (also as a mobile app?) for status recording and visualization as well as tracking of popular participation procedures.

The relevant data cannot be imported automatically. Instead, it must be entered manually by the users (initiators). Appropriate rights management should ensure that users can enter the necessary data via a standardized input form and manage their own process. In addition, users should be able to upload relevant documents and evidence and assign them to their procedures (document management).

The data entered must then be visualized in a uniform and automated manner. At the level of the individual processes, the most detailed representation possible (analogous to a circuit diagram) is required, in which the status for all relevant intermediate steps of the process is presented.

Overarching this, meaningful dashboards and reports are to be considered, which show developments and correlations.

In addition, interested parties should be able to track processes that are important to them and be automatically informed of status changes (WebAlert function).

The selection of the right technology in terms of ease of maintenance and extensibility (using open source components) is just as significant as the selection of licensing models (software, data, ...) that do not impair use and further development. Comprehensive and detailed documentation of the software is similarly relevant.

Following the end of the project, the aim is to transfer the solution to a non-profit status, which would benefit future public participation processes in Berlin.

Seminar program

There will be a preliminary meeting for the software project in the first week (October 18, 2021 - October 24, 2021). There will also be project meetings during the semester. Final presentations will be held in the last week (February 14, 2022 - February 20, 2022).

To be announced at the beginning of the semester.

Target audience

This software project is intended for computer science and data science students.

The official course website can be found here: https://www.wiwiss.fu-berlin.de/fachbereich/bwl/pwo/rothe/teaching/ma_tech-entrepreneurship.html

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.

- Claudia Eckert: IT-Sicherheit, 9. Auflage, De Gruyter Oldenbourg, 2014; - Ross Anderson: Security Engineering, 2. Auflage, Wiley, 2008. Weitere Literaturhinweise werden zu den einzelnen Themenblöcken bereitgestellt.

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.

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

• 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.

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.

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.

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

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

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

Dieses Modul beleuchtet, welche Rolle der „Faktor Mensch“ bei den Themen Sicherheit und Datenschutz (Usable Security & Privacy USP) spielt. Es wird eine Vielzahl von datenschutz- und sicherheitsrelevanten Themen im Zusammenhang mit verschiedenen Systemen und Benutzeroberflächen diskutiert. Während des Kurses werden die Studierenden sowohl theoretische als auch praktische Erfahrungen mit Methoden und Werkzeugen zur Identifizierung von Usability-, Sicherheits- und  Datenschutzproblemen sowie zur Erarbeitung von Lösungen derselben in verschiedenen Technologien sammeln.

Hinweis! Es ist beabsichtigt, dass dieses Modul kann in zwei verschiedenen Größen (5LP oder 10 LP) gewählt werden kann. Beide Größenoptionen umfassen Folgendes:

- Vorlesungen (2SWS)
- Übungen (2SWS)
- Leseaufgaben
- Vortrag
- Klausur

Die 10LP-Option dieses Moduls umfasst zusätzlich:
- Schriftliche Hausaufgaben
- Projekt, in dem das Wissen aus der Vorlesung und der Übung auf ein praktisches Problem angewandt wird, um ein aktuelles Problem auf dem Gebiet der USP zu untersuchen.

The official course website can be found here: https://www.wiwiss.fu-berlin.de/fachbereich/bwl/pwo/rothe/teaching/ma_tech-entrepreneurship.html

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.

- Claudia Eckert: IT-Sicherheit, 9. Auflage, De Gruyter Oldenbourg, 2014; - Ross Anderson: Security Engineering, 2. Auflage, Wiley, 2008. Weitere Literaturhinweise werden zu den einzelnen Themenblöcken bereitgestellt.

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.

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

• 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.

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.

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.

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

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

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

Dieses Modul beleuchtet, welche Rolle der „Faktor Mensch“ bei den Themen Sicherheit und Datenschutz (Usable Security & Privacy USP) spielt. Es wird eine Vielzahl von datenschutz- und sicherheitsrelevanten Themen im Zusammenhang mit verschiedenen Systemen und Benutzeroberflächen diskutiert. Während des Kurses werden die Studierenden sowohl theoretische als auch praktische Erfahrungen mit Methoden und Werkzeugen zur Identifizierung von Usability-, Sicherheits- und  Datenschutzproblemen sowie zur Erarbeitung von Lösungen derselben in verschiedenen Technologien sammeln.

Hinweis! Es ist beabsichtigt, dass dieses Modul kann in zwei verschiedenen Größen (5LP oder 10 LP) gewählt werden kann. Beide Größenoptionen umfassen Folgendes:

- Vorlesungen (2SWS)
- Übungen (2SWS)
- Leseaufgaben
- Vortrag
- Klausur

Die 10LP-Option dieses Moduls umfasst zusätzlich:
- Schriftliche Hausaufgaben
- Projekt, in dem das Wissen aus der Vorlesung und der Übung auf ein praktisches Problem angewandt wird, um ein aktuelles Problem auf dem Gebiet der USP zu untersuchen.

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.

- Claudia Eckert: IT-Sicherheit, 9. Auflage, De Gruyter Oldenbourg, 2014; - Ross Anderson: Security Engineering, 2. Auflage, Wiley, 2008. Weitere Literaturhinweise werden zu den einzelnen Themenblöcken bereitgestellt.

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.

Contents:

- Supervised learning

- Unsupervised learning

- Reinforcement learning

- Outlier detection

- Machine learning for high-dimensional data

- Machine learning in non-stationary environments

- Machine learning with imbalanced data

Dieses Modul beleuchtet, welche Rolle der „Faktor Mensch“ bei den Themen Sicherheit und Datenschutz (Usable Security & Privacy USP) spielt. Es wird eine Vielzahl von datenschutz- und sicherheitsrelevanten Themen im Zusammenhang mit verschiedenen Systemen und Benutzeroberflächen diskutiert. Während des Kurses werden die Studierenden sowohl theoretische als auch praktische Erfahrungen mit Methoden und Werkzeugen zur Identifizierung von Usability-, Sicherheits- und  Datenschutzproblemen sowie zur Erarbeitung von Lösungen derselben in verschiedenen Technologien sammeln.

Hinweis! Es ist beabsichtigt, dass dieses Modul kann in zwei verschiedenen Größen (5LP oder 10 LP) gewählt werden kann. Beide Größenoptionen umfassen Folgendes:

- Vorlesungen (2SWS)
- Übungen (2SWS)
- Leseaufgaben
- Vortrag
- Klausur

Die 10LP-Option dieses Moduls umfasst zusätzlich:
- Schriftliche Hausaufgaben
- Projekt, in dem das Wissen aus der Vorlesung und der Übung auf ein praktisches Problem angewandt wird, um ein aktuelles Problem auf dem Gebiet der USP zu untersuchen.

This class focuses on the design and analysis of algorithms, with topics including:

• general principles of algorithm design and analysis,
• 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.

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

Target audience

All Master and Bachelor students who are interested in algorithms.

Prerequisites

Basic familiarity with the design and analysis of algorithms.

In the lecture, we consider the implications of quantum computers for cryptography. To this end, we first introduce the operation of quantum computers and analyze various quantum algorithms. Highlights are the presentations of the quantum algorithms of Grover (to improve the cryptanalysis of symmetric methods) and Shor (to significantly improve the cryptanalysis of methods based on the factorization problem and the problem of computing the discrete logarithm).

Attention: The first class takes place on Tuesday, 02.11.2021.

Contents

• Complexity classes: P, NP, coNP, PH, L, SL, NL, coNL, PSPACE, NPSPACE, BPP, PP, ZPP, RP, #P, PARITY P, IP, AM, MA, EXP, NEXP, P/Poly, NC, ACC, BQP, PCP, MIP, etc. + oracles
• Theorems: Cook-Levin, Time- and Space-hierarchy, Ladner, Mahaney, Savitch, Immerman-Szelepcsényi, Karp-Lipton, Adleman, Sipser-Gács, Valiant-Vazirani, Baker-Gill-Solovay, Goldreich-Levin, PCP, parallel repetition, Goldwasser-Sipser, Nisan-Wigderson, Razborov-Smolensky, Razborov-Rudich, sum-check protocol, Håstad's switching lemma, expander mixin lemma, leftover hashing lemma, etc.
• Concepts: time, space, nondeterminism, advice, interaction, diagonalization, alternation, relativization, algebrization, naturalization, pseudo-randomness, error-correction, expander-graphs, discrete Fourier-analysis, etc.

Website

http://www.inf.fu-berlin.de/lehre/SS16/CCT/

• S. Arora und B. Barak. Computational Complexity: A Modern Approach. Cambridge University Press, 2009.
• O. Goldreich. Computational Complexity: A Conceptual Perspective. Cambridge University Press, 2008.
• C. Papadimitriou. Computational Complexity. Addison Wesley, 1994.
• M. Sipser. Introduction to the Theory of Computation. Thomson Press, 2005.
• I. Wegener. Komplexitätstheorie: Grenzen der Effizienz von Algorithmen. Springer Verlag, 2003.

Target Audience

M.S.-sutdents in Competer Science, Mathematics or similar courses of study. Afterwards, you can obtain a topic for a Master thesis.

Recommended Background 

Basic knowledge in Mathematics and Theoretical Computer Science: discrete Mathemtics, discrete probability theory, linear algebra, simple algebra and number theory, theory of algorithms, NP-completeness theory. More concretely: Contents of Mathematics for Computer Science, Theory of Computation, Algorithms and Data Structures, Advanced Algorithms

In this lecture, the fundamentals and paradigms of information-theoretical security (ITS) are conveyed, i.e. security mechanisms that cannot be traced back to "solving a difficult problem". ITS should come into play in future communication systems (e.g. evolutionary path from 5G to 6G or WiFi-6) and addresses essential aspects of new services such as the IoT, the tactile Internet, etc., especially with regard to scalable, fast and also user-manageable security ("Usability "). Another aspect that is frequently mentioned is security for the post-quantum age. Generally speaking, ITS uses the properties of the transmission channel in a targeted manner, e.g. through tap-proof coding or by generating a shared secret ("common information") about the specific properties of the complex electromagnetic wave propagation in the transmission medium.

Matthieu Bloch and Joao Barros: Physical Layer Security: From Information Theory to Security Engineering. Cambridge University Press, 2011

Attention: The first class takes place on Tuesday, 02.11.2021.

Contents

• Complexity classes: P, NP, coNP, PH, L, SL, NL, coNL, PSPACE, NPSPACE, BPP, PP, ZPP, RP, #P, PARITY P, IP, AM, MA, EXP, NEXP, P/Poly, NC, ACC, BQP, PCP, MIP, etc. + oracles
• Theorems: Cook-Levin, Time- and Space-hierarchy, Ladner, Mahaney, Savitch, Immerman-Szelepcsényi, Karp-Lipton, Adleman, Sipser-Gács, Valiant-Vazirani, Baker-Gill-Solovay, Goldreich-Levin, PCP, parallel repetition, Goldwasser-Sipser, Nisan-Wigderson, Razborov-Smolensky, Razborov-Rudich, sum-check protocol, Håstad's switching lemma, expander mixin lemma, leftover hashing lemma, etc.
• Concepts: time, space, nondeterminism, advice, interaction, diagonalization, alternation, relativization, algebrization, naturalization, pseudo-randomness, error-correction, expander-graphs, discrete Fourier-analysis, etc.

Website

http://www.inf.fu-berlin.de/lehre/SS16/CCT/

• S. Arora und B. Barak. Computational Complexity: A Modern Approach. Cambridge University Press, 2009.
• O. Goldreich. Computational Complexity: A Conceptual Perspective. Cambridge University Press, 2008.
• C. Papadimitriou. Computational Complexity. Addison Wesley, 1994.
• M. Sipser. Introduction to the Theory of Computation. Thomson Press, 2005.
• I. Wegener. Komplexitätstheorie: Grenzen der Effizienz von Algorithmen. Springer Verlag, 2003.

Target Audience

M.S.-sutdents in Competer Science, Mathematics or similar courses of study. Afterwards, you can obtain a topic for a Master thesis.

Recommended Background 

Basic knowledge in Mathematics and Theoretical Computer Science: discrete Mathemtics, discrete probability theory, linear algebra, simple algebra and number theory, theory of algorithms, NP-completeness theory. More concretely: Contents of Mathematics for Computer Science, Theory of Computation, Algorithms and Data Structures, Advanced Algorithms

In this lecture, the fundamentals and paradigms of information-theoretical security (ITS) are conveyed, i.e. security mechanisms that cannot be traced back to "solving a difficult problem". ITS should come into play in future communication systems (e.g. evolutionary path from 5G to 6G or WiFi-6) and addresses essential aspects of new services such as the IoT, the tactile Internet, etc., especially with regard to scalable, fast and also user-manageable security ("Usability "). Another aspect that is frequently mentioned is security for the post-quantum age. Generally speaking, ITS uses the properties of the transmission channel in a targeted manner, e.g. through tap-proof coding or by generating a shared secret ("common information") about the specific properties of the complex electromagnetic wave propagation in the transmission medium.

Matthieu Bloch and Joao Barros: Physical Layer Security: From Information Theory to Security Engineering. Cambridge University Press, 2011

In the lecture, we consider the implications of quantum computers for cryptography. To this end, we first introduce the operation of quantum computers and analyze various quantum algorithms. Highlights are the presentations of the quantum algorithms of Grover (to improve the cryptanalysis of symmetric methods) and Shor (to significantly improve the cryptanalysis of methods based on the factorization problem and the problem of computing the discrete logarithm).

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

• 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.

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.

• 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.

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

• propositional logic and mathematical proof techniques
• Boolean formulae und Boolean functions, disjunctive and conjunctive normal form, satisfiability, resolution calculus
• set theory:  sets, relations, equivalence and order relations, functions
• natural numbers, the induction principle, cardinal numbers
• first-order logic und mathematical structures
• combinatorics: counting techniques, binomial coefficents and Stirling numbers, recurrences, pigeon hole principle
• graph theory: graphs and their representations, paths and cycles in graphs, trees

• Christoph Meinel, Martin Mundhenk: Mathematische Grundlagen der Informatik, Teubner; 2. Auflage 2002
• Uwe Schöning: Logik für Informatiker, B.I.-Wissenschaftsverlag; 5. Auflage 2000
• Kenneth H. Rosen: Discrete Mathematics and its Applications, Mc-Graw Hill; 1999
• M. Aigner: Diskrete Mathematk, Vieweg, 5. Auflage 2004

Literature:

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

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

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

• Scheerer, Hans: Brückenkurs, Skript FU Berlin 2006.

Content:

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

Prerequisites:

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

• Siegfried Bosch, Lineare Algebra, 4. Auflage, Springer-Verlag, 2008;
• Gerd Fischer, Lernbuch Lineare Algebra und Analytische Geometrie, Springer-Verlag, 2017;
• Dirk Werner, Lineare Algebra. Vorlesungsskript.

Zu den Grundlagen

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

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

• 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

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

Literature:

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

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

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

• Scheerer, Hans: Brückenkurs, Skript FU Berlin 2006.

Content:

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

Prerequisites:

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

• Siegfried Bosch, Lineare Algebra, 4. Auflage, Springer-Verlag, 2008;
• Gerd Fischer, Lernbuch Lineare Algebra und Analytische Geometrie, Springer-Verlag, 2017;
• Dirk Werner, Lineare Algebra. Vorlesungsskript.

Zu den Grundlagen

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

Advanced module data visualization and data mining.

Wird bekannt gegeben.

Preliminary discussion date to be announced.

Clustering is a fundamental task in data science that often arises in real-world applications. In the past decades several alternative formulations of the clustering problem have been proposed. These have led to a variety of algorithms, both exact and approximate, using a broad range of optimization techniques such as local search, core-sets, linear programming, etc. Studying the inherent hardness of clustering has led to deep theoretical results, combining insights from geometry and graph theory.

In this seminar/reading group we will study representative and recent results related to clustering, with a focus on algorithmic and complexity aspects. We present/discuss one or two papers each week.

Requirements: ALP3/HA or similar algorithmic background, mathematical maturity.

Spezialliteratur aus Zeitschriften

Advanced module data visualization and data mining.

Wird bekannt gegeben.

Preliminary discussion date to be announced.

Description:

This seminar covers different topics from the research area of autonomous cars. We will focus on questions which can be the basis for Bachelor or Master theses as:

vision based person or vehicle recognition, map generation from trajectories, V2V and V2X communication, object tracking and prediction, sensory data fusion, localization using map matching, recognition of drivable areas and free spaces using stereo vision, path planning with A*, RRT, potential fields, automatic sensor calibration, map data formats.

Students can propose interesting topics, too. The seminar will be taught as a block course.

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.

Wird bekannt gegeben. / To be announced.

Target group

Students in the Master's or Bachelor's programme

Prerequisites

Good programming skills, introduction to database systems.

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.

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.

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

www.interdisciplinary-laboratory.hu-berlin.de

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.

Wird bekannt gegeben. / To be announced.

Target group

Students in the Master's or Bachelor's programme

Prerequisites

Good programming skills, introduction to database systems.

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.

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.

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

www.interdisciplinary-laboratory.hu-berlin.de