Courses
Aeronautics and Astronautics
AA 543 - Computational Fluid Dynamics
Numerical approximation of the inviscid compressible equations of fluid dynamics. Analysis of numerical accuracy, stability, and efficiency. Use of explicit, implicit, and flux split methods. Discussion of splitting, approximate factorization, discrete point, and finite volume approaches. Applications to the solution of simple hyperbolic systems of equations and the Euler equations.
AA 545 - Computational Methods for Plasmas
Develops the governing equations for plasma models - particle, kinetics, and MHD. Applies the governing equation to plasma dynamics through the PIC method and integration of fluid evaluation equations. Examines numerical solution to equilibrium configurations, and linear stability by energy principle and variational method.
Instructor: U. Shumlak
Applied Mathematics
AMATH 500A - High-Performance Scientific Computing
This course will introduce aspects of scientific computing and computational science that go beyond the Matlab-based introduction of AMath 301 or 352 and will introduce other languages (primarily Fortran 90/95/2003 and Python), debugging strategies, parallel computing (at the multi-core and cluster level), visualization tools for large data sets, and concepts such as Validation and Verification (V&V), uncertainty quantification (UQ), reproducible research, and scientific software design.
Instructor: R. LeVeque
http://kingkong.amath.washington.edu/trac/hpsc09
AMATH 571 - Spectral Methods
Analysis and application of spectral methods for the numerical solution of differential equations. Fourier methods and the FFT; collocation methods; polynomial interpolation and Chebyshev series; approximation theory and spectral accuracy; boundary conditions. Prerequisite: AMATH 584, AMATH 585, AMATH 586, or permission of instructor. Offered: Winter Quarter.
AMATH 574 - Conservation Laws and Finite Volume Methods
Theory of linear and nonlinear hyperbolic conservation laws modeling wave propagation in gases, fluids, and solids. Shock and rarefaction waves. Finite volume methods for numerical approximation of solutions; Godunov's method and high-resolution TVD methods. Stability, convergence, and entropy conditions. Prerequisite: AMATH 586 or permission of instructor. Offered: Winter Quarter.
http://www.amath.washington.edu/courses/574-winter-2009/
AMATH 581 - Scientific Computing
Project-oriented computational approach to solving problems arising in the physical/engineering sciences, finance/economics, medical, social and biological sciences. Problems requiring use of advanced MATLAB routines and toolboxes. Covers graphical techniques for data presentation and communication of scientific results. Prerequisite: Proficiency in basic MATLAB or AMATH 301, or permission of instructor.
http://www.amath.washington.edu/courses/
AMATH 584 - Applied Linear Algebra and Introductory Numerical Analysis
Numerical methods for solving linear systems of equations, linear least squares problems, matrix eigen value problems, nonlinear systems of equations, interpolation, quadrature, and initial value ordinary differential equations. Offered: jointly with MATH 584; A. Instructor Course Description: David George
http://www.amath.washington.edu/courses/
AMATH 585 - Numerical Analysis of Boundary Value Problems
Numerical methods for steady-state differential equations. Two-point boundary value problems and elliptic equations. Iterative methods for sparse symmetric and non-symmetric linear systems: conjugate-gradients, preconditioners. Prerequisite: AMATH 581 or MATH 584 which may be taken concurrently. Offered: jointly with MATH 585; Winter Quarter.
http://www.amath.washington.edu/courses/585-winter-2009/
AMATH 586 - Numerical Analysis of Time Dependent Problems
Numerical methods for time-dependent differential equations, including explicit and implicit methods for hyperbolic and parabolic equations. Stability, accuracy, and convergence theory. Spectral and pseudospectral methods. Prerequisite: AMATH 581 or AMATH 584. Offered: jointly with ATM S 581/MATH 586; Spring Quarter
http://www.amath.washington.edu/courses/586-spring-2009/
Astronomy
Numerical Methods of Astrophysics
This is a hands-on course to learn methods for numerically solving problems that arise in astrophysics. Some programming experience is required. An emphasis is placed on high performance. Topics include ordinary differential equations, root finding, optimization, Monte-Carlo methods, basic data structures and algorithms, and parallel techniques. Text: "Numerical Recipes" by Press et al.
Instructor: T. Quinn
Computer Science & Engineering
CSE 446/546 – Machine Learning and Data Mining
Explores methods for designing systems that learn from data and improve with experience. Supervised learning and predictive modeling: decision trees, rule induction, nearest neighbors, Bayesian methods, neural networks, support vector machines, and model ensembles. Unsupervised learning and clustering. (CSE 446 for CSE majors only, or by permission of instructor.)
http://www.cs.washington.edu/education/courses/446/
http://www.cs.washington.edu/education/courses/546/
CSEP 546 – Data Mining (Professional Masters Program)
Methods for identifying valid, novel, useful, and understandable patterns in data. Induction of predictive models from data: classification, regression, probability estimation. Discovery of clusters and association rules.
http://www.cs.washington.edu/education/courses/csep546/
CSE 544 – Principles of Database Systems
Data models and query languages (SQL, datalog, OQL). Relational databases, enforcement of integrity constraints. Object-oriented databases and object-relational databases. Principles of data storage and indexing. Query-execution methods and query optimization algorithms. Static analysis of queries and rewriting of queries using views. Data integration. Data mining. Principles of transaction processing.
Instructor: M. Balazinska
http://www.cs.washington.edu/education/courses/544/
CSE 490H - Scalable Systems: Design, Implementation and Use of Large Scale Clusters
This course will "put the meat on the bones" of our popular Hadoop programming course. We will discuss the software techniques employed to construct and program reliable highly-scalable systems. You should think of this course as covering "cool current topics in computer systems". You will read a number of recent research papers. Programming exercises, as in previous instances of the course, will involve Hadoop running on a cluster provided by Google; there will also be an Amazon Web Services exercise.
Instructor: E. Lazowska
http://www.cs.washington.edu/education/courses/490h/
CSE 524 - Parallel Algorithms
As well as teaching fundamental parallel algorithms, this course offers hands on experience with various parallel programming paradigms from MPI to ZPL and MapReduce. Text: Principles of Parallel Programming, Calvin Lin and Lawrence Snyder, Addison Wesley, 2008.
Instructor: L. Snyder
http://www.cs.washington.edu/education/courses/524/
Medical Education & Biomedical Informatics
MEBI 531 - Life and Death Computing
MEBI 531 addresses the complex software design issues that come up in biomedical and health informatics, programming for safety critical applications in medicine and health care, as well as in the application of computing to unlock the secrets of life. Examples from biology, medicine and health motivate software engineering topics such as: use of abstraction layers, design of tightly coupled but modular and extensible software, formal models and safety in real time control of medical equipment, design of network application protocols, integration of diverse biomedical data sources.
Instructor: I. Kalet
http://www.radonc.washington.edu/medinfo/mebi531/
MEBI 550 - Knowledge Representation and Applications
MEBI 550 deals with the principles of knowledge representation and reasoning, with application to biology, medicine and health. Many of the examples will use the Common Lisp programming language, but prior knowledge of Lisp is not assumed. Other programming and knowledge representation languages will also be introduced, such as Prolog.
Instructor: I. Kalet
http://www.radonc.washington.edu/medinfo/mebi531/