Search result: Catalogue data in Autumn Semester 2019
Computer Science Master  | ||||||
 Focus Courses | ||||||
| Focus Courses General Studies | ||||||
| Seminar in General Studies | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|---|
| 263-4505-00L | Algorithms for Large-Scale Graph Processing The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | M. Ghaffari | |
| Abstract | This is a theory seminar, where we present and discuss recent algorithmic developments for processing large-scale graphs. In particular, we focus on Massively Parallel Computation (MPC) algorithms. MPC is a clean and general theoretical framework that captures the essential aspects of computational problems in large-scale processing settings such as MapReduce, Hadoop, Spark, Dryad, etc. | |||||
| Learning objective | This seminar familiarizes students with foundational aspects of large-scale graph processing, and especially the related algorithmic tools and techniques. In particular, we discuss recent developments in the area of Massively Parallel Computation. This is a mathematical abstraction of practical large-scale processing settings such as MapReduce, and it has been receiving significant attention over the past few years. The seminar assumes no particular familiarity with parallel computation. However, we expect that all the students are comfortable with basics of algorithms design and analysis, as well as probability theory. In the course of the seminar, the students learn how to structure a scientific presentation (in English) which covers the key ideas of a paper, while omitting the less significant details. | |||||
| Content | The seminar will cover a number of the recent papers on Massively Parallel Computation. As mentioned above, no familiarity with parallel computation is needed and all the relevant background information will be explain by the instructor in the first lecture. | |||||
| Literature | The papers will be presented in the first session of the seminar. | |||||
| Computer Science Elective Courses The Elective Computer Science Courses can be selected from all Master level courses offered by D-INFK. | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
| 252-0293-00L | Wireless Networking and Mobile Computing | W | 4 credits | 2V + 1U | S. Mangold | |
| Abstract | This course gives a detailed overview about the wireless and mobile standards and summarizes the state of the art for Wi-Fi 802.11, Cellular 5G, and Internet-of-Things, including new topics such audio communication, cognitive radio, and visible light communications. The course combines lectures with a set of assignments in which students are asked to work with a simple JAVA simulation software. | |||||
| Learning objective | The objective of the course is to learn about the general principles of wireless communications, including physics, frequency spectrum regulation, and standards. Further, the most up-to-date standards and protocols used for wireless LAN IEEE 802.11, Wi-Fi, Internet-of-Things, sensor networks, cellular networks, visible light communication, and cognitive radios, are analyzed and evaluated. Students develop their own add-on mobile computing algorithms to improve the behavior of the systems, using a Java-based event-driven simulator. We also hand out embedded systems that can be used for experiments for optical communication. | |||||
| Content | Wireless Communication, Wi-Fi, Internet-of-Things, 5G, Standards, Regulation, Algorithms, Radio Spectrum, Cognitive Radio, Mesh Networks, Optical Communication, Visible Light Communication | |||||
| Lecture notes | The script will be made available from the course webpage. | |||||
| Literature | (1) The course webpage (look for Stefan Mangold's site) (2) The Java 802 protocol emulator "JEmula802" from https://bitbucket.org/lfield/jemula802 (3) WALKE, B. AND MANGOLD, S. AND BERLEMANN, L. (2006) IEEE 802 Wireless Systems Protocols, Multi-Hop Mesh/Relaying, Performance and Spectrum Coexistence. New York U.S.A.: John Wiley & Sons. Nov 2006. (4) BERLEMANN, L. AND MANGOLD, S. (2009) Cognitive Radio for Dynamic Spectrum Access . New York U.S.A.: John Wiley & Sons. Jan 2009. (5) MANGOLD, S. ET.AL. (2003) Analysis of IEEE 802.11e for QoS Support in Wireless LANs. IEEE Wireless Communications, vol 10 (6), 40-50. | |||||
| Prerequisites / Notice | Students should have interest in wireless communication, and should be familiar with Java programming. | |||||
| 252-3610-00L | Smart Energy | W | 4 credits | 2G + 1A | F. Mattern, V. C. Coroama | |
| Abstract | The lecture covers the role of ICT for sustainable energy usage. It starts out with a general background on the current landscape of energy generation and consumption and outlines concepts of the emerging smart grid. The lecture combines technologies from ubiquitous computing and traditional ICT with socio-economic and behavioral aspects and illustrates them with examples from actual applications. | |||||
| Learning objective | Participants become familiar with the diverse challenges related to sustainable energy usage, understand the principles of a smart grid infrastructure and its applications, know the role of ubiquitous computing technologies, can explain the challenges regarding security and privacy, can reflect on the basic cues to induce changes in consumer behavior, develop a general understanding of the effects of a smart grid infrastructure on energy efficiency. Participants will apply the learnings in a course-accompanying project, which includes both programming and data analysis. The lecture further includes interactive exercises, case studies and practical examples. | |||||
| Content | - Background on energy generation and consumption; characteristics, potential, and limitations of renewable energy sources - Introduction to energy economics - Smart grid and smart metering infrastructures, virtual power plants, security challenges - Demand management and home automation using ubiquitous computing technologies - Changing consumer behavior with smart ICT - Benefits and challenges of a smart energy system - Smart heating, electric mobility | |||||
| Literature | Will be provided during the course, though a good starting point is "ICT for green: how computers can help us to conserve energy" from Friedemann Mattern, Thosten Staake, and Markus Weiss (available at http://www.vs.inf.ethz.ch/publ/papers/ICT-for-Green.pdf). | |||||
| 263-0600-00L | Research in Computer Science  Only for Computer Science MSc. | W | 5 credits | 11A | Professors | |
| Abstract | Independent project work under the supervision of a Computer Science Professor. | |||||
| Learning objective | Independent project work under the supervision of a Computer Science Professor. | |||||
| Prerequisites / Notice | Only students who fulfill one of the following requirements are allowed to begin a research project: a) 1 lab (interfocus course) and 1 focus course b) 2 core focus courses c) 2 labs (interfocus courses) A task description must be submitted to the Student Administration Office at the beginning of the work. | |||||
| 227-0423-00L | Neural Network Theory | W | 4 credits | 2V + 1U | H. Bölcskei, E. Riegler | |
| Abstract | The class focuses on fundamental mathematical aspects of neural networks with an emphasis on deep networks: Universal approximation theorems, capacity of separating surfaces, generalization, reproducing Kernel Hilbert spaces, support vector machines, fundamental limits of deep neural network learning, dimension measures, feature extraction with scattering networks | |||||
| Learning objective | After attending this lecture, participating in the exercise sessions, and working on the homework problem sets, students will have acquired a working knowledge of the mathematical foundations of neural networks. | |||||
| Content | 1. Universal approximation with single- and multi-layer networks 2. Geometry of decision surfaces 3. Separating capacity of nonlinear decision surfaces 4. Generalization 5. Reproducing Kernel Hilbert Spaces, support vector machines 6. Deep neural network approximation theory: Fundamental limits on compressibility of signal classes, Kolmogorov epsilon-entropy of signal classes, covering numbers, fundamental limits of deep neural network learning 7. Learning of real-valued functions: Pseudo-dimension, fat-shattering dimension, Vapnik-Chervonenkis dimension 8. Scattering networks | |||||
| Lecture notes | Detailed lecture notes will be provided as we go along. | |||||
| Prerequisites / Notice | This course is aimed at students with a strong mathematical background in general, and in linear algebra, analysis, and probability theory in particular. | |||||
| 227-0778-00L | Hardware/Software Codesign Does not take place this semester. | W | 6 credits | 2V + 2U | L. Thiele | |
| Abstract | The course provides advanced knowledge in the design of complex computer systems, in particular embedded systems. Models and methods are discussed that are fundamental for systems that consist of software and hardware components. | |||||
| Learning objective | The course provides advanced knowledge in the design of complex computer systems, in particular embedded systems. Models and methods are discussed that are fundamental for systems that consist of software and hardware components. | |||||
| Content | The course covers the following subjects: (a) Models for describing hardware and software components (specification), (b) Hardware-Software Interfaces (instruction set, hardware and software components, reconfigurable computing, heterogeneous computer architectures, System-on-Chip), (c) Application specific instruction sets, code generation and retargetable compilation, (d) Performance analysis and estimation techniques, (e) System design (hardware-software partitioning and design space exploration). | |||||
| Lecture notes | Material for exercises, copies of transparencies. | |||||
| Literature | Peter Marwedel, Embedded System Design, Springer, ISBN-13 978-94-007-0256-1, 2011. Wayne Wolf. Computers as Components. Morgan Kaufmann, ISBN-13: 978-0123884367, 2012. | |||||
| Prerequisites / Notice | Prerequisites for the course is a basic knowledge in the following areas: computer architecture, digital design, software design, embedded systems | |||||
| 227-0781-00L | Low-Power System Design | W | 6 credits | 2V + 2U | J. Beutel | |
| Abstract | Introduction to low-power and low-energy design techniques from a systems perspective including aspects both from hard- and software. The focus of this lecture is on cutting across a number of related fields discussing architectural concepts, modeling and measurement techniques as well as software design mainly using the example of networked embedded systems. | |||||
| Learning objective | Knowledge of the state-of-the-art in low power system design, understanding recent research results and their implication on industrial products. | |||||
| Content | Designing systems with a low energy footprint is an increasingly important. There are many applications for low-power systems ranging from mobile devices powered from batteries such as today's smart phones to energy efficient household appliances and datacenters. Key drivers are to be found mainly in the tremendous increase of mobile devices and the growing integration density requiring to carefully reason about power, both from a provision and consumption viewpoint. Traditional circuit design classes introduce low-power solely from a hardware perspective with a focus on the power performance of a single or at most a hand full of circuit elements. Similarly, low-power aspects are touched in a multitude of other classes, mostly as a side topic. However in successfully designing systems with a low energy footprint it is not sufficient to only look at low-power as an aspect of second class. In modern low-power system design advanced CMOS circuits are of course a key ingredient but successful low-power integration involves many more disciplines such as system architecture, different sources of energy as well as storage and most importantly software and algorithms. In this lecture we will discuss aspects of low-power design as a first class citizen introducing key concepts as well as modeling and measurement techniques focusing mainly on the design of networked embedded systems but of course equally applicable to many other classes of systems. The lecture is further accompanied by a reading seminar as well as exercises and lab sessions. | |||||
| Lecture notes | Exercise and lab materials, copies of lecture slides. | |||||
| Literature | A detailed reading list will be made available in the lecture. | |||||
| Prerequisites / Notice | Knowledge in embedded systems, system software, (wireless) networking, possibly integrated circuits, and hardware software codesign. | |||||
| Elective Courses Students can individually chose from the entire Master course offerings from ETH Zurich, EPF Lausanne, the University of Zurich and - but only with the consent of the Director of Studies - from all other Swiss universities. For further details, refer to Art. 31 of the Regulations 2009 for the Master Program in Computer Science. | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
| 263-2900-00L | How To Give Strong Technical Presentations Does not take place this semester. | Z | 0 credits | M. Püschel | ||
| Abstract | ||||||
| Learning objective | Wherever possible I illustrate by example and present the material in a way to make it immediately applicable. The goal is to provide the knowledge that enables the participants, whether beginner or experienced presenter, to further improve their presentation skills and hence their impact whenever they step in front of an audience. | |||||
| Content | This course covers all aspects of delivering strong presentations. I explain common mistakes, what works and what does not, and why. Then I discuss structure and content as well as a set of fundamental principles from graphic design that make slides communicate effectively. These principles also apply to the presentation and visualization of data which is covered in some detail. Finally, I give some useful tips on the use of Powerpoint that simplify the creation of strong presentations. | |||||
| 151-3217-00L | Coaching Students (Basic Training) | W | 1 credit | 1G | B. Volk, R. P. Haas, M. Lehner | |
| Abstract | Aim is enhancement of knowledge and competency regarding coaching skills. Participants should be active coaches of a student team. Topics: Overview of the roles and mind set of a coach as, introduction into coaching methodology, mutual learning and reflecting of participants coaching expertise and situations. | |||||
| Learning objective | - Basic knowledge about role and mindset of a coach - Basic Knowledge and reflection about classical coaching situations - Inspiration and mutual learning from real coaching sessions (mutual peer observation) | |||||
| Content | Basic knowledge about role and mindset of a coach - Introduction into coaching: definition & models - Introduction into the coaching process and team building phases - Role of coaches between examinator, tutor and ""friend"" First steps building up personal coaching competencies, i.e. active listening, asking questions, giving feedback - Competencies in theoretical models - Coaching competencies: exercises and reflection Some Reflection and exchange of experiences about personal coaching situations - Exchange of experiences in the lecture group - Mutual peer observations | |||||
| Lecture notes | Slides, script and other documents will be distributed electronically (access only for participants registered to this course) | |||||
| Literature | Please refer to lecture script. | |||||
| Prerequisites / Notice | Participants (Students, PhD Students, Postdocs) should be actively coaching students. | |||||
| 263-0610-00L | Direct Doctorate Research Project Only for Direct Doctorate Students | O | 15 credits | 23A | Professors | |
| Abstract | Direct Doctorate Students join a research group of D-INFK in order to acquire a broader view of the different research groups and areas. | |||||
| Learning objective | Students extend their knowledge of the different research topics and improve their scientific approach of working on an actual research project. | |||||
| Content | 2nd semester students join a research group of D-INFK in order to acquire a broader view of the different research groups and areas. The research group chosen must not be identical with the one, in which the thesis project is conducted. | |||||
| Prerequisites / Notice | Please be aware that the research project and the master's thesis have to be coached by two different research groups! | |||||
| 263-0620-00L | Direct Doctorate Research Plan Only for Direct Doctorate Students | O | 15 credits | 23A | Professors | |
| Abstract | The research plan aims at planning and structuring a student's research work and thesis. It further contributes to the student's ability to write research proposals. | |||||
| Learning objective | The student has to present the research plan to the faculty members in order to defend his/her research goals, but also to demonstrate a solid knowledge on the background literature as well as the planned and alternative procedures to follow. | |||||
| Internship | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
| 252-0700-00L | Internship Only for Computer Science MSc. | W | 0 credits | external organisers | ||
| Abstract | The internship must be at least 10 weeks long and can be undertaken in a Swiss or a foreign company. | |||||
| Learning objective | An internship provides opportunities to gain experience in an industrial environment and creates a network of contacts. | |||||
| Prerequisites / Notice | To register the internship, please submit a document to the Student Administration Office containing the following information at the latest two weeks after beginning the intership: - a detailed task description: task, technologies, milestones etc. - start and end date of the internship - supervisor: name and academic degree | |||||
| GESS Science in Perspective | ||||||
| » see GESS Science in Perspective: Language Courses ETH/UZH | ||||||
| » see GESS Science in Perspective: Type A: Enhancement of Reflection Capability | ||||||
| » Recommended GESS Science in Perspective (Type B) for D-INFK. | ||||||
| Master's Thesis | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
| 263-0800-00L | Master's Thesis Only students who fulfill the following criteria are allowed to begin with their master thesis: a. successful completion of the bachelor programme; b. fulfilling any additional requirements necessary to gain admission to the master programme; c. "Inter focus courses" (12 credits) completed; d. "Focus courses" (26 credits) completed (including seminar). | O | 30 credits | 64D | Supervisors | |
| Abstract | The Master's thesis concludes the study programme. Thesis work should prove the students' ability to independent, structured and scientific working. | |||||
| Learning objective | To work independently and to produce a scientifically structured work under the supervision of a Computer Science Professor. | |||||
| Content | Independent project work supervised by a Computer Science professor. Duration 6 months. | |||||
| Prerequisites / Notice | Supervisor must be a professor at D-INFK or affiliated, see https://inf.ethz.ch/people/faculty.html | |||||
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