Search result: Course units in Spring Semester 2018
Data Science Master | ||||||
Core Courses | ||||||
Data Analysis | ||||||
Information and Learning | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|---|
227-0434-10L | Mathematics of Information | W | 8 credits | 3V + 2U + 2A | H. Bölcskei | |
Statistics | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
401-3632-00L | Computational Statistics | W | 10 credits | 3V + 2U | M. H. Maathuis | |
Data Management | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
261-5110-00L | Optimization for Data Science | W | 8 credits | 3V + 2U + 2A | B. Gärtner, D. Steurer | |
Core Electives | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
151-0566-00L | Recursive Estimation | W | 4 credits | 2V + 1U | R. D'Andrea | |
227-0150-00L | Energy-Efficient Parallel Computing Systems for Data Analytics Previously called "Advanced System-on-chip Design: Integrated Parallel Computing Architectures" | W | 6 credits | 4G | L. Benini | |
227-0224-00L | Stochastic Systems | W | 4 credits | 2V + 1U | F. Herzog | |
227-0420-00L | Information Theory II Does not take place this semester. | W | 6 credits | 2V + 2U | A. Lapidoth | |
227-0558-00L | Principles of Distributed Computing | W | 6 credits | 2V + 2U + 1A | R. Wattenhofer, M. Ghaffari | |
252-0211-00L | Information Security | W | 8 credits | 4V + 3U | D. Basin, S. Capkun | |
252-0526-00L | Statistical Learning Theory | W | 6 credits | 2V + 3P | J. M. Buhmann | |
252-0538-00L | Shape Modeling and Geometry Processing | W | 5 credits | 2V + 1U + 1A | S. Coros | |
252-0579-00L | 3D Vision | W | 4 credits | 3G | T. Sattler, M. R. Oswald | |
252-3005-00L | Natural Language Understanding | W | 4 credits | 2V + 1U | T. Hofmann, M. Ciaramita | |
261-5130-00L | Research in Data Science | W | 6 credits | 13A | Professors | |
263-0008-00L | Computational Intelligence Lab Only for master students, otherwise a special permission by the study administration of D-INFK is required. | W | 8 credits | 2V + 2U + 1A | T. Hofmann | |
263-2925-00L | Program Analysis for System Security and Reliability | W | 5 credits | 2V + 1U + 1A | M. Vechev | |
263-3710-00L | Machine Perception Students, who have already taken 263-3700-00 User Interface Engineering are not allowed to register for this course! | W | 5 credits | 2V + 1U + 1A | O. Hilliges | |
401-0674-00L | Numerical Methods for Partial Differential Equations Not meant for BSc/MSc students of mathematics. | W | 8 credits | 4V + 2U + 1A | R. Hiptmair | |
401-3052-05L | Graph Theory | W | 5 credits | 2V + 1U | B. Sudakov | |
401-3052-10L | Graph Theory | W | 10 credits | 4V + 1U | B. Sudakov | |
401-3602-00L | Applied Stochastic Processes Does not take place this semester. | W | 8 credits | 3V + 1U | not available | |
401-3622-00L | Regression | W | 8 credits | 4G | P. L. Bühlmann | |
401-4632-15L | Causality | W | 4 credits | 2G | N. Meinshausen | |
401-4904-00L | Combinatorial Optimization | W | 6 credits | 2V + 1U | R. Zenklusen | |
401-6102-00L | Multivariate Statistics Does not take place this semester. | W | 4 credits | 2G | not available | |
701-0104-00L | Statistical Modelling of Spatial Data | W | 3 credits | 2G | A. J. Papritz | |
Interdisciplinary Electives | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
101-0478-00L | Measurement and Modelling of Travel Behaviour | W | 6 credits | 4G | K. W. Axhausen | |
103-0228-00L | Multimedia Cartography Prerequisite: Successful completion of Cartography III (103-0227-00L). | W | 4 credits | 3G | H.‑R. Bär, R. Sieber | |
103-0247-00L | Mobile GIS and Location-Based Services | W | 5 credits | 4G | P. Kiefer | |
103-0255-01L | Geodata Analysis | W | 2 credits | 2G | D. Jonietz | |
227-0945-10L | Cell and Molecular Biology for Engineers II This course is part II of a two-semester course. Knowledge of part I is required. | W | 3 credits | 2G | C. Frei | |
261-5111-00L | Asset Management: Advanced Investments (University of Zurich) Der Kurs muss direkt an der UZH belegt werden. UZH Modulkürzel: MFOEC207 Beachten Sie die Einschreibungstermine an der UZH: Link | W | 3 credits | 2V | University lecturers | |
261-5120-00L | Computational Biomedicine II | W | 4 credits | 3P | G. Rätsch | |
263-3501-00L | Advanced Computer Networks | W | 5 credits | 2V + 2U | A. Singla, P. M. Stüdi | |
363-1000-00L | Financial Economics | W | 3 credits | 2V | A. Bommier | |
363-1091-00L | Social Data Science | W | 3 credits | 2G | D. Garcia Becerra | |
401-3629-00L | Quantitative Risk Management | W | 4 credits | 2V | P. Cheridito | |
401-3888-00L | Introduction to Mathematical Finance A related course is 401-3913-01L Mathematical Foundations for Finance (3V+2U, 4 ECTS credits). Although both courses can be taken independently of each other, only one will be recognised for credits in the Bachelor and Master degree. In other words, it is not allowed to earn credit points with one for the Bachelor and with the other for the Master degree. | W | 10 credits | 4V + 1U | M. Schweizer | |
401-3936-00L | Data Analytics for Non-Life Insurance Pricing | W | 4 credits | 2V | C. M. Buser, M. V. Wüthrich | |
401-4658-00L | Computational Methods for Quantitative Finance: PDE Methods | W | 6 credits | 3V + 1U | C. Schwab | |
401-8915-00L | Advanced Financial Economics (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: MFOEC206 Mind the enrolment deadlines at UZH: Link | W | 6 credits | 4G | University lecturers | |
636-0702-00L | Statistical Models in Computational Biology | W | 6 credits | 2V + 1U + 2A | N. Beerenwinkel | |
701-0412-00L | Climate Systems | W | 3 credits | 2G | R. Knutti, I. Medhaug | |
701-1216-00L | Numerical Modelling of Weather and Climate | W | 4 credits | 3G | C. Schär, U. Lohmann | |
701-1226-00L | Inter-Annual Phenomena and Their Prediction | W | 2 credits | 2G | C. Appenzeller | |
701-1252-00L | Climate Change Uncertainty and Risk: From Probabilistic Forecasts to Economics of Climate Adaptation | W | 3 credits | 2V + 1U | D. N. Bresch, R. Knutti | |
851-0252-06L | Introduction to Social Networks: Theory, Methods and Applications Number of participants limited to 40. This course is intended for students interested in data analysis and with basic knowledge of inferential statistics. | W | 3 credits | 2G | C. Stadtfeld, A. Vörös | |
Data Science Lab This course unit will be given in HS18 for the first time according to programme regulations 2016 Data Science MSc. | ||||||
Seminar | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
263-3830-00L | Software Defined Networking: The Data Centre Perspective | W | 2 credits | 2S | T. Roscoe, D. Wagenknecht-Dimitrova | |
263-3840-00L | Hardware Architectures for Machine Learning | W | 2 credits | 2S | G. Alonso, T. Hoefler, O. Mutlu, C. Zhang | |
401-3620-18L | Student Seminar in Statistics: Nonparametric Estimation under Shape-Constraints Number of participants limited to 22. Mainly for students from the Mathematics Bachelor and Master Programmes who, in addition to the introductory course unit 401-2604-00L Probability and Statistics, have heard at least one core or elective course in statistics. | W | 4 credits | 2S | F. Balabdaoui, P. L. Bühlmann, M. H. Maathuis, N. Meinshausen, S. van de Geer | |
GESS Science in Perspective | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
» Recommended Science in Perspective (Type B) for D-INFK | ||||||
» see Science in Perspective: Type A: Enhancement of Reflection Capability | ||||||
» see Science in Perspective: Language Courses ETH/UZH | ||||||
851-0740-00L | Big Data, Law, and Policy Number of participants limited to 35 Students will be informed by 4.3.2018 at the latest | W | 3 credits | 2S | S. Bechtold, T. Roscoe, E. Vayena | |
Master's Thesis | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
261-0800-00L | Master's Thesis The minimal prerequisites for the Master’s thesis registration are: Completed Bachelor’s program All additional requirements completed (additional requirements, if any, are listed in the admission decree) Minimum degree requirements fulfilled of the course categories Data Analysis and Data Management and overall 50 credits obtained in the course category Core Courses Data Science Lab (14 credits) completed | O | 30 credits | 64D | Professors |