Online Course Material:
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each week to get announcements, weekly lecture slides, and assignments.
Assignments will include simple tasks done in
Microsoft Excel (or in Matlab, or in the
equivalent *free* software package
download the software here).
All homework assignments will be based on skills taught within the
course. The emphasis will be on exploring how scientific data and equations are represented and solved
within a computer, and how computers are used to move from equations and data into knowledge.
All assigments are designed for students with no programming experience and with limited
mathematical backgrounds (high school algebra).
Instructors may submit Exam Papers, Homework solutions,
or any other student assignment to either
or the SafeAssign
plagiarism-detection services, in compliance with all of the following:
GMU policy, Provost approval, and the
GMU Honor Code.
Courses designed to meet the Natural Science Gen Ed requirement must address
Courses in this category are intended to provide students with an understanding of natural science. The critical approach of the scientific method, the relation of theory and experiment, the use of quantitative and qualitative information, and the development and elaboration of major ideas in science are addressed.
(3 Credits) Introduction to the use of computers in scientific discovery through simulations and data analysis. Covers historical development and current trends in the field. Satisfies General Education Requirement: Natural science Nonlab.
Additional Course Description:
This course explores the connections between the on-going advances across the natural sciences
and the rapid advances in computing. Students will learn about the cutting edge results in the
Computational and Data Sciences, as well as develop a greater understanding of the tools, methods,
and techniques that make these results possible. Examples familiar to students and from the frontiers
of science will be presented to demonstrate how computational tools are changing our scientific
approach in domains from genetics to cosmology. Students will learn how we use computers to
analyze data sets and create complex numerical simulations across the disciplines to see the common
challenges in using computers as part of the scientific method. No mathematical background is
assumed for students in the course, other than successful completion of the Math competency exam.
Qualitative results will be emphasized, to show the problems, algorithms, and challenges facing
Appropriate score on the math placement test.
Class Participation (the lowest 2 scores will be dropped)
Homework (the lowest 2 scores will be dropped)
Course Objectives: By the end of the course, the student will be able to
Understand how the scientific method is used across the sciences;
Use computers to investigate simple scientific problems using both data and simulations;
Solve simple scientific equations;
Describe how data are acquired, processed, analyzed, and visualized in a variety of scientific domains;
Explain how simulations are used across the natural sciences, and understand their limitations; and
Describe the connections between advances in computing and advances in the natural sciences.