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UNI 4030V Machine Learning & Visualization Using R





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iCatalog Home UNI 4030V Machine Learning & Visualization Using R
(Last Modified:24-Mar-2022)

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Description
This is a George Mason University (GMU) course provided via DAU with GMU professors. The artificial intelligence area of machine learning provides the engine behind predictive analytics. This course provides a technical overview of the various disciplines within data analytics currently in use within OSD ADVANA, OSD (A&S) DaVE, USA/USAF PMRT and Navy RDAIS teams.
Objectives
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Target Attendees
NH-III/IV and equivalent defense acquisition workforce members, including business - cost estimating, business - financial management, contracting, engineering & technical management, lifecycle logistics, program management, and test & evaluation functional areas
Prerequisite(s)
See Notes
Predecessor Course(s)
Predecessor Predecessor Course Title PDS Code Expires On
None None None None
Course Length
40 student hours, over the course of 8 weeks (see Notes)
Additional Course Information
Delivery Mode Virtual Instructor Led Training
Equivalent Courses N/A
ACE Recommended Credits N/A
PDS Code B3I
Walk-ins Authorized No
Pre-work required No
First Offering 7/19/2021
Continuing Education Units   0
Continuous Learning Points  40
Reservist Retirement Points  0
Historical Allocations Mouse Over for Past CEU/CLPs
Fulfillment Eligible N/A
Technical Requirements Click Here
Notes
  • This course is restricted to DoD employees. Walk-ins NOT authorized.
  • This course involves some programming using the R programming language. Some entry level programming experience in a language such as R, Python, HTML, Java. If you do not have some programming experience, we recommend taking Johns Hopkins University "R Programming" course with Coursera. If you need this course, contact the course manager at william.parker@dau.edu and he will provide an account to access the Coursera pre-requisite course.
  • Virtual classes are conducted via MS Teams for Education.

  • Course design:
  • Virtual instructor-led (VILT) session each week (Tuesday 12:30-4:00pm; optional office hours avail on demand)
  • Weekly assignments between live sessions

  • DAU Catalog