Syllabus
(print version in PDF)
Prerequisites:
Analytic
Geometry and
Calculus (Math
113)
Credits:
3
Date:
Tuesday
and Thursday
Time: 09:00 AM to
10:15 AM
Place:
Research
Building 1, room 301
Instructors:
Prof.
Jie
Zhang
Contact
Info: (703)993-1998
(phone), jzhang7@gmu.edu
(e-mail)
Office
Hour: 10:30 AM to 11:30
AM, Thursday, or by appointment
Office:
Room 351, Research
Bldg 1
Teaching
Assistant: Dr.
Joseph
Marr
Contact info:
jmarr2@gmu.edu
(e-mail)
Dr. Marr will grade homework and exams and answer
questions that
you pose on BlackBoard
Description:
This is a
newly approved course (April, 2010) for science majors at GMU
and fulfills the General Education
Information Technology
requirement. In this course, students
will learn how to use computers to solve practical scientific problems.
Topics
will include creating effective scientific presentations, analysis of
experimental data, on-line literature, data/information ethics,
scientific
modeling, and communication/collaboration tools. Beyond just
introducing
computing tools, this course will equip students with the knowledge and
confidence they need to make productive use of future hardware and
software
both as students and throughout their career
Content:
- Computer fundamentals
- Binary representation of data, data storage, logic tables and
circuits.
- Measurements
- Sensors, sensor limits, calibration, analog to digital converters,
signal-to-noise, precision, accuracy,
and bias.
- Basic Data Structures
– tables, spreadsheets, arrays, and
- Visualization
– Data representation types, creating visualizations,
creating and visualizing images
- Data analysis
- statistical analysis, data fitting
- On-line information systems
– scientific databases, SQL, queries, data storage, data and
information quality, literature searches
- Data Ethics
– ethical use of publications, data, and code, ethical issues
in scientific data including human subject research, confidentiality,
presentation of data
- Scientific simulation
– using computers to simulate dynamical systems, mathematical
models, iteration, verification, validation
- Effective scientific
publications and collaborations
– creating effective visualization to communicate ideas,
tables, citations, computational tools for effective writing,
presentations, and collaborations
- The
future of scientific
computing –
data-intensive computing, cloud computing, quantum computing, and
cyber-enabled science & discovery limits to numerical
resolution, data storage, processing, data communications, networking,
programming concepts, algorithms, programming languages
Software
Tools: Excel, Matlab
Homework: There will be a weekly
homework. Homework will be multiple choice and short answer. The
grading scheme
for short answer questions is 0/1/2, where 2 = substantial
understanding of concepts
and/or correct answer and at most one grammatical error; 1 = an
understanding
of underlying concepts, with some gaps and/or almost correct answer and
at most
two grammatical errors; 0 = little or no understanding of concepts
and/or
incorrect answer. Answers should be 1-5 sentences in length.
Project: There will be one
comprehensive project throughout the semester. The project will consist
of multiple phases, each of which has its own
requirement and due date.
Exams: There will be one
midterm
and one final exam.
Grading: Homework (25%), Project
(20%),
Midterm (25%), Final Exam (25%), Class Participation (5%)
Class
URL: http://blackboard.gmu.edu/ and http://solar.gmu.edu/teaching/2010_CDS130/
Text
Book: None - no suitable
textbook exists for this
course.
On-line notes and web-based content will be used to supplement the
lectures and
in-class assignments.
Honor
Code: As in
any class, you are allowed to study with other students. However, tests
and
homework assignments must be completed on your own unless stated
specifically
in the assignment guidelines. In some assignments, you will be directed
toward
on-line sources for papers, data and code. If these data, code, or
papers are
used for a project, then you MUST cite where it came from.
Specifically, you
may not copy any text, computer code, image, data or any other material
from
the Internet or any other source and represent it as your own. Any
material
that is taken in whole or in part from any other source (including
web-pages) that
is not properly cited will be treated as a violation of Mason's
academic honor
code and will be submitted to the honor committee for adjudication, as
will
other violations of the honor code.