Search result: Catalogue data in Autumn Semester 2016

Computational Science and Engineering Bachelor Information
Bachelor Studies (Programme Regulations 2012)
Basic Courses
Block G1
NumberTitleTypeECTSHoursLecturers
401-0353-00LAnalysis IIIO4 credits2V + 1UE. Kowalski
AbstractIn this lecture we treat problems in applied analysis. The focus lies on the simplest cases of three fundamental types of partial differential equations of second order: the Laplace equation, the heat equation and the wave equation.
Objective
Content1.) Klassifizierung von PDE's
- linear, quasilinear, nicht-linear
- elliptisch, parabolisch, hyperbolisch

2.) Quasilineare PDE
- Methode der Charakteristiken (Beispiele)

3.) Elliptische PDE
- Bsp: Laplace-Gleichung
- Harmonische Funktionen, Maximumsprinzip, Mittelwerts-Formel.
- Methode der Variablenseparation.

4.) Parabolische PDE
- Bsp: Wärmeleitungsgleichung
- Bsp: Inverse Wärmeleitungsgleichung
- Methode der Variablenseparation

5.) Hyperbolische PDE
- Bsp: Wellengleichung
- Formel von d'Alembert in (1+1)-Dimensionen
- Methode der Variablenseparation

6.) Green'sche Funktionen
- Rechnen mit der Dirac-Deltafunktion
- Idee der Green'schen Funktionen (Beispiele)

7.) Ausblick auf numerische Methoden
- 5-Punkt-Diskretisierung des Laplace-Operators (Beispiele)
LiteratureY. Pinchover, J. Rubinstein, "An Introduction to Partial Differential Equations", Cambridge University Press (12. Mai 2005)

Zusätzliche Literatur:
Erwin Kreyszig, "Advanced Engineering Mathematics", John Wiley & Sons, Kap. 8, 11, 16 (sehr gutes Buch, als Referenz zu benutzen)
Norbert Hungerbühler, "Einführung in die partiellen Differentialgleichungen", vdf Hochschulverlag AG an der ETH Zürich.
G. Felder:Partielle Differenzialgleichungen.
https://people.math.ethz.ch/~felder/PDG/
Prerequisites / NoticePrerequisites: Analysis I and II, Fourier series (Komplexe Analysis)
402-0811-00LProgramming Techniques for Scientific Simulations IO5 credits4GM. Troyer
AbstractThis lecture provides an overview of programming techniques for scientific simulations. The focus is on advances C++ programming techniques and scientific software libraries. Based on an overview over the hardware components of PCs and supercomputer, optimization methods for scientific simulation codes are explained.
Objective
401-0663-00LNumerical Methods for CSE Information O7 credits4V + 2UR. Hiptmair
AbstractThe course gives an introduction into fundamental techniques and algorithms of numerical mathematics which play a central role in numerical simulations in science and technology. The course focuses on fundamental ideas and algorithmic aspects of numerical methods. The exercises involve actual implementation of numerical methods in C++.
Objective* Knowledge of the fundamental algorithms in numerical mathematics
* Knowledge of the essential terms in numerical mathematics and the
techniques used for the analysis of numerical algorithms
* Ability to choose the appropriate numerical method for concrete problems
* Ability to interpret numerical results
* Ability to implement numerical algorithms afficiently
Content1. Direct Methods for linear systems of equations
2. Least Squares Techniques
3. Data Interpolation and Fitting
4. Filtering Algorithms
8. Approximation of Functions
9. Numerical Quadrature
10. Iterative Methods for non-linear systems of equations
11. Single Step Methods for ODEs
12. Stiff Integrators
Lecture notesLecture materials (PDF documents and codes) will be made available to participants:

Lecture document: https://people.math.ethz.ch/~grsam/HS16/NumCSE/NumCSE16.pdf

Lecture Git repository: https://gitlab.math.ethz.ch/NumCSE/NumCSE

Tablet classroom notes: http://www.sam.math.ethz.ch/~grsam/HS16/NumCSE/NCSE16_Notes/

Lecture recording: http://www.video.ethz.ch/lectures/d-math/2016/autumn/401-0663-00L.html

Homework problems: https://people.math.ethz.ch/~grsam/HS16/NumCSE/NCSEProblems.pdf
LiteratureU. ASCHER AND C. GREIF, A First Course in Numerical Methods, SIAM, Philadelphia, 2011.

A. QUARTERONI, R. SACCO, AND F. SALERI, Numerical mathematics, vol. 37 of Texts in Applied Mathematics, Springer, New York, 2000.

W. Dahmen, A. Reusken "Numerik für Ingenieure und Naturwissenschaftler", Springer 2006.

M. Hanke-Bourgeois "Grundlagen der Numerischen Mathematik und des wissenschaftlichen Rechnens", BG Teubner, 2002

P. Deuflhard and A. Hohmann, "Numerische Mathematik I", DeGruyter, 2002
Prerequisites / NoticeThe course will be accompanied by programming exercises in C++ relying on the template library EIGEN. Familiarity with C++, object oriented and generic programming is an advantage. Participants of the course are expected to learn C++ by themselves.
Block G2
NumberTitleTypeECTSHoursLecturers
401-0603-00LStochastics (Probability and Statistics)O4 credits2V + 1UM. H. Maathuis
AbstractThis class covers the following concepts: random variables, probability, discrete and continuous distributions, joint and conditional probabilities and distributions, the law of large numbers, the central limit theorem, descriptive statistics, statistical inference, inference for normally distributed data, point estimation, and two-sample tests.
ObjectiveKnowledge of the basic principles of probability and statistics.
ContentIntroduction to probability theory, some basic principles from mathematical statistics and basic methods for applied statistics.
Lecture notesLecture notes
LiteratureLecture notes
252-0834-00LInformation Systems for Engineers Information O4 credits2V + 1UR. Marti
AbstractFoundations of information systems from a user's viewpoint. The focus is on structured data: relational databases, the data language SQL, designing relational databases. Additional topics: Information Retrieval (searching documents), and estimating their relevance and authority with respect to free-text queries; XML as a format for data exchange; Characteristics and processing of "Big Data"
ObjectiveFollowing the course should enable students to

1. answer non-trivial queries on existing relational databases by formulating (entry-level) SQL statements, as well as to add new database content and to update or delete existing content,

2. formalize facts as perceived in the real world in terms of the entity-relationship model, and derive a set of normalized relations (tables) which define the structure of a relational database

3. explain how a database management system (DBMS) essentially works and what kind of services it provides

4. understand how a web search engine such as Google basically works

5. know and apply the core concepts to structure and query XML-documents

6. list the characteristics of "Big Data" and know the basics of processing "Big Data"
ContentDie Lehrveranstaltung vermittelt Grundlagen und Konzepte von Informationssystemen aus der Sicht eines Anwenders.

Im Zentrum stehen relationale Datenbanksysteme, die Abfrage- und Datenmanipulationssprache SQL, sowie der Entwurf bzw. die Strukturierung relationaler Datenbanken. Dieser Stoff wird auch in praktischen Übungen vertieft.

Weitere Themen sind der Umgang mit unstrukturierten und semistrukturierten Daten, die Integration von Daten aus verschiedenen autonomen Informationssystemen, sowie eine Übersicht der Architektur von Datenbanksystemen.

Inhalt:
1. Einleitung.
2. Das Relationenmodell.
3. Die Abfrage- und Datenmanipulationssprache SQL.
4. Entwurf relationaler Datenbanken mit Hilfe von Entity-Relationship Diagrammen. Grundideen der Normalisierung von Relationen.
5. Architektur relationaler Datenbanksysteme.
6. Information Retrieval: Suche von (Text-) Dokumenten. Indexing, Stopwort-Elimination und Stemming. Boole'sches Retrieval und das Verktorraum-Modell.
7. Web Information Retrieval: Web-Crawling. Ausnutzen der Web-Links zwischen Web-Seiten (Page Ranking). Das Zusammenspiel von Crawling, klassischem Information Retrieval und Page Ranking.
8. Modellierung semi-strukturierter Daten mit XML und einfache Anfragen mit XPath und XQuery.
9. Zugriff auf SQL-Datenbanken aus Programmen, Transaktionen.
10. Neuere Entwicklungen: "Big Data", CAP Theorem, Hadoop (HDFS als verteiltes File System, Map-Reduce als Verarbeitungskonzept)
LiteratureVorlesungsunterlagen (PowerPoint Folien, teilweise auch zusätzlicher Text) werden auf der Web-Site publiziert. Der Kauf eines Buches wird nicht vorausgesetzt.

Das Buch "Datenbanksysteme: Eine Einführung, 9. Auflage" von Alfons Kemper und André Eickler, erschienen im Oldenbourg Verlag, 2013, enthält den behandelten Stoff, und vieles mehr (Umfang: 848 Seiten!). Die Vorlesung ist jedoch nur teilweise auf das Buch abgestimmt.

Als englischsprachiges Werk kann z.B.

A. Silberschatz, H.F. Korth, S. Sudarshan:
Database System Concepts, 6th Edition, McGraw-Hill, 2010.

empfohlen werden (Umfang: 1349 Seiten).
Prerequisites / NoticeVoraussetzung:
Elementare Kenntnisse von Mengenlehre und logischen Ausdrücken.
Kenntnisse und minimale Programmiererfahrung in einer Programmiersprache wie z.B. Pascal, C, C++, Java, Python.
401-0647-00LIntroduction to Mathematical Optimization Information O5 credits2V + 1UD. Adjiashvili
AbstractIntroduction to basic techniques and problems in mathematical optimization, and their applications to problems in engineering.
ObjectiveThe goal of the course is to obtain a good understanding of some of the most fundamental mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. The students will also practice applying the learned models to problems in engineering.
ContentTopics covered in this course include:
- Linear programming (simplex method, duality theory, shadow prices, ...).
- Basic combinatorial optimization problems (spanning trees, network flows, knapsack problem, ...).
- Modelling with mathematical optimization: applications of mathematical programming in engineering.
LiteratureInformation about relevant literature will be given in the lecture.
Prerequisites / NoticeThis course is meant for students who did not already attend the course "Mathematical Optimization", which is a more advance lecture covering similar topics and more.
Block G3
All course units within Block G3 are offered in the spring semester.
Block G4
Students that enrol for the second year in the CSE Bachelor Programme and whose first year examination did not involve the subject "Physics I" will instead take the "Physics I and II" (402-0043-00L and 402-0044-00L) courses with performance assessment as a yearly course.
NumberTitleTypeECTSHoursLecturers
402-0043-00LPhysics IW4 credits3V + 1UT. Esslinger
AbstractIntroduction to the concepts and tools in physics with the help of demonstration experiments: mechanics of point-like and ridged bodies, periodic motion and mechanical waves.
ObjectiveThe concepts and tools in physics, as well as the methods of an experimental science are taught. The student should learn to identify, communicate and solve physical problems in his/her own field of science.
ContentMechanics (motion, Newton's laws, work and energy, conservation of momentum, rotation, gravitation, fluids)
Periodic Motion and Waves (periodic motion, mechanical waves, acoustics).
Lecture notesThe lecture follows the book "Physics" by Paul A. Tipler.
LiteraturePaul A. Tipler and Gene P. Mosca, Physics (for Scientists and Engineers), W. H. Freeman and Company
Prerequisites / NoticePrerequisites: Mathematics I & II
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