Operational Edge Computing for UAS
Deploy AI and machine learning at the tactical edge using NVIDIA Jetson Orin Nano hardware — no ML background required.
Operational Edge Computing for UAS
Deploy AI and machine learning at the tactical edge. Develop capability to process sensor data locally, make autonomous decisions, and operate effectively in disconnected environments without cloud connectivity.
Program Overview
This program develops practical edge computing skills for UAS operators. Training emphasizes deployable AI systems that operate in bandwidth-constrained, disconnected operational environments.
Key Focus Areas:
- Edge computing hardware (Jetson Nano/Xavier, similar platforms)
- Computer vision and object detection (YOLO, similar frameworks)
- Real-time target recognition and tracking
- Autonomous decision-making at the edge
- Mission-specific AI model deployment
Who Should Attend
Primary Audience:
- UAS operators requiring advanced autonomy
- Intelligence analysts integrating AI workflows
- Technical personnel supporting tactical UAS
- Research and development teams
- Advanced operator training cadre
Prerequisites: Basic UAS operations experience, basic computing literacy
Training Approach
Hands-on deployment of edge computing systems on actual UAS platforms. Students configure hardware, deploy AI models, and validate performance in operational scenarios.
Program Outcomes
Upon completion, operators demonstrate capability to:
- Configure edge computing hardware for UAS deployment
- Deploy and validate AI models for specific missions
- Troubleshoot edge computing systems in field conditions
- Assess AI performance and reliability
- Integrate edge AI into tactical operations
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Questions?
Email: info@forgeandflightacademy.com
Related Programs:
- FFA-501: Advanced Autonomy Employment - Complex autonomous missions
- FFA-201: AI Fundamentals - Non-technical overview
Course Details
| Duration | 5 days (40 contact hours) |
| Format | Facility-based (Fayetteville, NC) |
| Prerequisites | FFF-401 or equivalent. Basic Python or scripting experience helpful. |
| Target Audience | Technical operators, engineers, research lab personnel, autonomy developers |
| Scheduling | Contact us to schedule. Limited cohort size — 6 students max. |
Frequently Asked Questions
What does FFA-401 teach?
FFA-401 teaches operators how to deploy AI and machine learning capabilities at the tactical edge using NVIDIA Jetson Orin Nano hardware. Students learn real-time target recognition, autonomous decision pipeline configuration, and edge computing for disconnected operations.
Do I need a machine learning background for FFA-401?
No machine learning background is required. FFA-401 is designed for operators who need to employ AI payloads, not data scientists who build models. The course focuses on operational deployment and configuration on real hardware.
What hardware is used in FFA-401?
Each student works with an NVIDIA Jetson Orin Nano compute module. The hardware is provided as part of the course and students keep it upon graduation.
How long is FFA-401?
FFA-401 is a 5-day program covering 40 contact hours. It is delivered facility-based in Fayetteville, NC.
What are the prerequisites for FFA-401?
FFF-401 or equivalent UAS operational experience is recommended. Basic Python or scripting experience is helpful but not required. Operators who have completed FFF-401 are well-prepared for FFA-401.
Ready to Schedule This Course?
All training proposals are customized to your organization’s requirements, operational timeline, and location preference.
Ready to Schedule This Course?
All training proposals are customized to your organization's requirements, operational timeline, and location preference. We respond within 48 hours.