New sUAS Courses Offered at TNCC

Thomas Nelson Community College is offering courses in small unmanned aircraft systems (sUAS), also known as drones. These classes will provide training to fast track you into a career in sUAS. These classes can also help you develop skills in sUAS to add to your current skill set to prepare for jobs in multiple careers.

These four unmanned systems (UMS) courses are engaging and interactive and align with employer needs in sUAS.

UMS 107 Remote Pilot Ground School

  • Learn the rules and regulations to legally fly drones.  The course will prepare you to take the FAA Part 107 Remote Pilot Certification Exam.  No pre-requisite is required to take the class.
  • Two sections of the class are available during the first 8-week session (August 23rd – October 18th). In-person on Monday evenings from 5:30 – 8 pm (Hampton campus) OR fully online.

 

UMS 111 Introduction to Small UAS (sUAS) – The Manual Flight sUAS class. 

  • TNCC will provide drones for students to use.  No-pre-requisite is required to take the class.
  • The class is offered during the first 8-week session (August 23rd – October 18th).  Meets in person on Thursday mornings from 9:30 am – 12:15 pm on the Williamsburg campus.

 

UMS 177 sUAS Components and Maintenance.

  • Students learn about the components of a drone and build a drone in class.
  • Class is offered on the Hampton campus in person on Wednesday evenings from 4 – 6:50 pm (September 21st – December 15th).  No pre-requisite is required.

 

UMS 211 Advanced Small UAS (sUAS) – The Autonomous Flight class. 

  • UMS 111 is a prerequisite to take this class.
  • Class is offered on the Williamsburg campus in person on Thursday afternoons from 2 – 4:50 pm.  TNCC will provide drones for students to use.

 

These courses were developed with support in part by the GeoTEd-UAS project, http://geoted-uas.org/. Partners in GeoTEd-UAS include Virginia Space Grant Consortium, Germanna Community College, Virginia Tech, and the Virginia Community College System.

GeoTEd-UAS is funded by the NSF (NSF DUE #1601614; #2000715).