Search result: Catalogue data in Spring Semester 2018

Computational Science and Engineering Master Information
Course Units for Additional Admission Requirements
The courses below are only available for MSc students with additional admission requirements.
NumberTitleTypeECTSHoursLecturers
252-0232-AALSoftware Design Information
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-6 credits13RD. Gruntz
AbstractThe course Software Design presents and discusses design patterns regularly used to solve problems in object oriented design and object oriented programming. The presented patterns are illustrated with examples from the Java libraries and are applied in a project.
ObjectiveThe students
- know the principles of object oriented programming and can apply these.
- know the most important object oriented design patterns.
- can apply design patterns to solve design problems.
- discover in a given design the use of design patterns.
ContentThis course makes an introduction to object oriented programming. As programming language Java is used. The focus of this course however is object oriented design, in particular design patterns. Design patterns are solutions to recurring design problems. The discussed patterns are illustrated with examples from the Java libraries and are applied in the context of a project.
Literature- Gamma, Helm, Johnson, Vlissides; Design Patterns: Elements of Reusable Object-Oriented Software; Prentice Hall;ISBN 978-0201633610
- Freeman, Freeman, Sierra; Head First Design Patterns, Head First Design Patterns; O'Reilly; ISBN 978-0596007126
406-0353-AALAnalysis III
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-4 credits9RF. Da Lio
AbstractThe 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
LiteratureReference books and notes

Main books:

Giovanni Felder: "Partielle Differenzialgleichungen für Ingenieurinnen und Ingenieure" (Download PDF: Link ),
Erwin Kreyszig: "Advanced Engineering Mathematics", John Wiley & Sons, just chapters 11, 16.


Extra readings:

Norbert Hungerbühler: "Einführung in die partiellen Differentialgleichungen", vdf Hochschulverlag AG an der ETH Zürich,
Yehuda Pinchover, Jacob Rubinstein: "Partial Differential Equations", Cambridge University Press 2005.


For reference/complement of the Analysis I/II courses:

Christian Blatter: Ingenieur-Analysis (Download PDF)
Prerequisites / NoticeThe precise content changes with the examiner. Candidates must therefore contact the examiner in person before studying the material.
406-0603-AALStochastics (Probability and Statistics)
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-4 credits9RM. Kalisch
AbstractIntroduction to basic methods and fundamental concepts of statistics and
probability theory for non-mathematicians. The concepts are presented on
the basis of some descriptive examples. The course will be based on the
book "Statistics for research" by S. Dowdy et.al. and on the
book "Introductory Statistics with R" by P. Dalgaard.
ObjectiveThe objective of this course is to build a solid fundament in probability
and statistics. The student should understand some fundamental concepts and
be able to apply these concepts to applications in the real
world. Furthermore, the student should have a basic knowledge of the
statistical programming language "R". The main topics of the course are:
- Introduction to probability
- Common distributions
- Binomialtest
- z-Test, t-Test
- Regression
ContentFrom "Statistics for research":
Ch 1: The Role of Statistics
Ch 2: Populations, Samples, and Probability Distributions
Ch 3: Binomial Distributions
Ch 6: Sampling Distribution of Averages
Ch 7: Normal Distributions
Ch 8: Student's t Distribution
Ch 9: Distributions of Two Variables [Regression]

From "Introductory Statistics with R":
Ch 1: Basics
Ch 2: Probability and distributions
Ch 3: Descriptive statistics and tables
Ch 4: One- and two-sample tests
Ch 5: Regression and correlation
Literature"Statistics for research" by S. Dowdy et. al. (3rd
edition); Print ISBN: 9780471267355; Online ISBN: 9780471477433; DOI:
10.1002/0471477435;
From within the ETH, this book is freely available online under:
Link

"Introductory Statistics with R" by Peter Dalgaard; ISBN
978-0-387-79053-4; DOI: 10.1007/978-0-387-79054-1
From within the ETH, this book is freely available online under:
Link
406-0663-AALNumerical Methods for CSE Information
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-7 credits15RR. Alaifari
AbstractIntroduction into fundamental techniques and algorithms of numerical mathematics which play a central role in numerical simulations in science and technology.
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 in C++
Content1. Computing with Matrices and Vectors
2. Direct Methods for Linear Systems of Equations
3. Direct Methods for Linear Least Squares Problems
4. Filtering Algorithms
5. Data Interpolation and Data Fitting in 1D
6. Approximation of Functions in 1D
7. Numerical Quadrature
8. Iterative Methods for Non-linear Systems of Equations
12. Numerical Integration - Single Step Methods
13. Single Step Methods for Stiff Initial Value Problems
Lecture notesLink
LiteratureW. 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
U. Ascher and C. Greif "A first course in Numerical Methods"
Prerequisites / NoticeExamination will be conducted at the computer and will involve coding in C++/Eigen.
A course covering the material is taught in English every autumn term (course unit 401-0663-00L). Course documents, exercises and examinations are available online.
529-0483-AALStatistical Physics and Computer Simulation
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

All other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-4 credits9RM. Reiher
AbstractPrinciples and applications of statistical mechanics and equilibrium molecular dynamics, Monte Carlo simulation, Stochastic dynamics.
Exercises using a MD simulation program to generate ensembles and subsequently calculate ensemble averages.
ObjectiveIntroduction to statistical mechanics with the aid of computer simulation, development of skills to carry out statistical mechanical calculations using computers and interpret the results.
ContentPrinciples and applications of statistical mechanics and equilibrium molecular dynamics, Monte Carlo simulation, Stochastic dynamics.
Exercises using a MD simulation program to generate ensembles and subsequently calculate ensemble averages.
Literaturesee "Course Schedule"
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