ISC 1057
Computational Thinking
T R 2:00-3:15 217 HCB
Janet Peterson
This introductory course considers the question of how computers have come to imitate many kinds of human intelligence. The answer seems to involve our detecting patterns in nature, but also in being able to detect patterns in the very way we think. This course will look at some popular computational methods that shape our lives, and try to explain the ideas that make them work. This course has been approved to satisfy the Liberal Studies Quantitative/Logical Thinking requirement.
ISC 3313
Introduction to Scientific Computing
M W F 12:20-1:10 152 DSL
Alan Lemmon
This course introduces the student to the science of computations. Topics cover algorithms for standard problems in computational science, as well as the basics of an object-oriented programming language, to facilitate the student’s implementation of algorithms. The computer language will be Java. Prerequisites: MAC 2312 (or permission of the instructor).
ISC 4220
Algorithms for Science Applications I
T R 2:00-3:15 152 DSL, R 3:15-5:45 (Lab) 152 DSL
Sachin Shanbhag
Basic computational algorithms including interpolation, approximation, integration, differentiation, and linear systems solution presented in the context of science problems. The lab component includes algorithm implementation for simple problems in the sciences and applying visualization software for interpretation of results. Corequisite: ISC 3222; Prerequisite: MAC 2312.
ISC 4304
Programming for Science Applications
T R 11:00-12:15 152 DSL, T 3:15-5:45 (Lab) 152 DSL
Peter Beerli
Provides knowledge of a scripting language that serves as a front end to popular packages and frameworks, along with a compiled language such as C++. Topics include the practical use of an object-oriented scripting and compiled language for scientific programming applications. There is a laboratory component for the course; concepts learned are illustrated in several science applications. Prerequisites: MAC 2312, COP 3014 or ISC 3313.
ISC 5236/4933
Applied Groundwater Modeling
M W F 1:25-2:15 152 DSL
Ming Ye
This course introduces groundwater modeling theory and practice, with emphasis on model construction, simulation, as well as calibration, and using state-of-the-art modeling tools. Students learn basic concepts and governing equations of fluid flow in porous media, computational algorithms of solving the equations, and mathematical methods of inverse modeling. Essential statistics of evaluating quality of model simulations is introduced and examples of synthetic cases and real-world applications are used. Prerequisite: ISC 5226.
ISC 5307
Scientific Visualization
M W F 11:15-12:05 152 DSL
Xiaoqiang Wang
This course covers the theory and practice of scientific visualization. Students learn how to use state-of-the-art visualization toolkits, create their own visualization tools, represent both 2-D and 3-D data sets, and evaluate the effectiveness of their visualizations. Prerequisite: ISC 5305.
ISC 5316
Applied Computational Science II
T R 12:30-1:45 152 DSL, M 2:30-5:00 (Lab) 152 DSL
Bryan Quaife
Provides students with high performance computational tools to investigate problems in science and engineering with an emphasis on combining them to accomplish more complex tasks. Topics include numerical methods for partial differential equations, optimization, statistics, and Markov chain Monte Carlo methods. Prerequisite: ISC 5315.
ISC 5415/4933
Computational Space Physics
M W F 10:10-11:00 152 DSL
Tomasz Plewa
Introduction to numerical methods in the context of observational and theoretical astrophysics. Interpolation,approximation, minimization and optimization, solution of linear systems of equations, random number generation, function integration, numerical differentiation, numerical integration of ordinary differential equations, stiff systems of ODEs, survey of methods for PDEs (Poisson equation, heat diffusion, and hydrodynamics). Prerequisites: MAC 2312, or the permission of the instructor; basic programming skills in Fortran, C, or C++.
ISC 5935/4933
Intro to Density Functional Theory
T R 9:30-10:45 152 DSL
Chen Huang
The course is designed for materials scientists, chemists, physicists, and applied mathematicians who are seeking to know both the basic concept and certain advanced topics in density functional theory. Density functional theory is widely used nowadays in both industry and academia to simulate various properties of materials and molecules, such as electronic properties, crystal structures, and chemical reactions. In this course, we will learn how to solve realistic materials problems using density functional theory and the underlying theories.