Download AIT 580 - Office of the Provost

For approval of new courses and deletions or
modifications to an existing course.
Course Approval Form
registrar.gmu.edu/facultystaff/curriculum
Action Requested:
Course Level:
x Create new course
Inactivate existing course
Modify existing course (check all that apply)
Title
Prereq/coreq
Other:
College/School:
Submitted by:
Subject Code:
Credits
Schedule Type
Undergraduate
x Graduate
Repeat Status
Restrictions
Grade Type
Department:
Ext:
3-2799
VSE
Robert T. Quinn
Number:
AIT
Effective Term:
580
(Do not list multiple codes or numbers. Each course proposal must
have a separate form.)
Title:
Applied Information Technology
Email: [email protected]
x
Fall
Spring
Summer
Year
2013
Current
Big Data & Advanced Analytics
Banner (30 characters max including spaces)
New
Credits:
x
(check one)
Grade Mode:
Fixed
Variable
x
(check one)
3
or
to
Repeat Status:
x
Not Repeatable (NR)
Repeatable within degree (RD)
Repeatable within term (RT)
(check one)
Regular (A, B, C, etc.)
Satisfactory/No Credit
Special (A, B C, etc. +IP)
Prerequisite(s):
Graduate Standing
Schedule Type:
(check one)
LEC can include
LAB or RCT
x
Maximum credits
allowed:
Lecture (LEC)
Lab (LAB)
Recitation (RCT)
Internship (INT)
Corequisite(s):
Independent Study (IND)
Seminar (SEM)
Studio (STU)
Instructional Mode:
x 100% face-to-face
Hybrid: ≤ 50% electronically delivered
100% electronically delivered
Restrictions Enforced by System: Major, College, Degree, Program, etc. Include Code.
Are there equivalent course(s)?
Yes
x No
If yes, please list
Catalog Copy for NEW Courses Only (Consult University Catalog for models)
Description (No more than 60 words, use verb phrases and present tense)
Notes (List additional information for the course)
Course provides an overview of Big Data and its use in commercial, scientific,
governmental and other applications. Topics include technical and non-technical
disciplines required to collect, process and use enormous amounts of data available
from numerous sources. Lectures cover system acquisition, law and policy, and
ethical issues. It includes brief discussions of technologies involved in collecting,
mining, analyzing and using results.
Indicate number of contact hours:
Hours of Lecture or Seminar per week: 3
Hours of Lab or Studio:
When Offered: (check all that apply)
x Spring
x Fall
Summer
Approval Signatures
11/26/2012
Date
Robert T. Quinn
Department Approval
11/26/2012
Date
College/School Approval
If this course includes subject matter currently dealt with by any other units, the originating department must circulate this proposal for review by
those units and obtain the necessary signatures prior to submission. Failure to do so will delay action on this proposal.
Unit Name
Unit Approval Name
Unit Approver’s Signature
Date
For Graduate Courses Only
Graduate Council Member
Provost Office
Graduate Council Approval Date
For Registrar Office’s Use Only: Banner_____________________________Catalog________________________________
revised 11/8/11
Syllabus
AIT 580 Big Data & Advanced Analytics
Description:
Course provides an overview of Big Data and its use in commercial, scientific, governmental and other applications. Topics include
technical and non-technical disciplines required to collect, process and use enormous amounts of data available from numerous
sources. Lectures cover system acquisition, law and policy, and ethical issues. It includes brief discussions of technologies involved
in collecting, mining, analyzing and using results.
Prerequisite:
Graduate standing
Texts:
D.J. Patil, Building Data Science Teams, O’Reilly Media, ISBN: 978-1-449-31623-5.
http://isrc.gmu.edu/ExecLectureSeries/ExecLectureSeries.html “Big Data in the U.S. Intelligence Community”, a compendium of the
impact Big Data and Massive Analytics creates on every facet of an organization.
Harvard Business Review, September 2012
Instructors:
Charles Randy Howard, Ph.D.
Department of Applied Information Technology
[email protected], (703) 899-3608
Grading:
Team Project: 40%
Lab Project: 40%
Class Participation: 10%
Peer Evaluation: 10%
Topics
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
Introduction , Definitions, Terms and Uses
Law, Policy, Regulation of Data and Information
Technology Development and System Acquisition
Big Data Collection and Transmission, Cloud Computing
Data Types
Data Quality and Data Management
Metadata
Data Mining
Analytic Techniques and Pathologies
Data Visualization
Ethical Challenges and Provocations in Big Data
Case Studies
Future trends in Big Data