Edge AI for Computer Vision Training in Riyadh

Edge AI for Computer Vision Training in Riyadh, Saudi Arabia

This course provides hands-on training in using Edge AI for computer vision applications, focusing on deploying vision-based AI models.

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Edge AI for Computer Vision Training is a professional training program delivered by ProgNXT in Riyadh, Saudi Arabia. ProgNXT, a globally recognized corporate training provider in 55+ countries, offers this Edge AI for Computer Vision Training course with hands-on, instructor-led sessions. This course provides hands-on training in using Edge AI for computer vision applications, focusing on deploying vision-based AI models on...

Expert Panel

Designed by the ProgNXT AI & Data Science Expert Panel, specializing in Generative AI, Machine Learning, and ChatGPT applications

ProgNXT AI & Data Science Expert Panel

Course Code: KQA45
21 Hrs
Last Updated: April 2026

Course Rating5/5

This course provides hands-on training in using Edge AI for computer vision applications, focusing on deploying vision-based AI models on resource-constrained edge devices. Participants will explore real-time image and video processing, object detection, face recognition, and model optimization for hardware like Raspberry Pi, Jetson Nano, and mobile devices.

Welcome to the official Edge AI for Computer Vision Training certification program in Riyadh, Saudi Arabia. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge locally. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 21 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Basic understanding of AI/ML and computer vision
Familiarity with Python programming
Optional: Experience with TensorFlow, PyTorch, or OpenCV

By the end of the training, participants will be able to develop, optimize, and deploy computer vision models on edge devices, achieving real-time performance for various applications such as surveillance, smart devices, industrial automation, and more.

Understanding computer vision workflows in Edge AI
Building and optimizing models for edge devices
Running real-time vision models on hardware
Using tools like TensorFlow Lite, OpenVINO, or Jetson SDK
Creating efficient edge applications with cameras and sensors

Image classification and object detection at the edge
Model conversion and quantization techniques
Hardware acceleration and inference tuning
Use case analysis (security, health, industry)
Deployment workflow and real-time testing

ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

Foundations of Edge AI and Computer Vision

Introduction to Edge AI and Computer Vision

What is Edge AI?
Why computer vision at the edge matters
Benefits: low latency, privacy, offline processing

Edge AI Hardware and Software Stack

Overview of devices: Raspberry Pi, Jetson Nano, Coral Dev Board, mobile
AI toolkits: TensorFlow Lite, OpenVINO, PyTorch Mobile
Vision libraries: OpenCV, MediaPipe, YOLO models

Computer Vision Basics for the Edge

Image classification vs object detection vs segmentation
Key concepts: bounding boxes, inference time, accuracy
Example walkthrough: classifying handwritten digits on a Pi

Model Optimization and Vision Use Cases

Optimizing AI Models for Edge Deployment

Quantization, pruning, model simplification
Model conversion for TFLite and ONNX
Testing for performance and accuracy trade-offs

Real-Time Object Detection on Edge Devices

YOLOv5 and SSD models for detection
Running detection models with live video input
Comparing accuracy vs. speed on edge hardware

Use Case Walkthroughs

Smart surveillance: person detection
Retail: shelf monitoring
Manufacturing: fault detection
Medical: monitoring patient posture

Deployment, Integration, and Final Project

Building Vision Applications on the Edge

Creating pipelines with camera, processing, display
Managing input/output in real-time
Logging, alerts, and remote monitoring

Face Recognition and People Tracking (Optional Advanced)

Running face detection models
Adding simple tracking or recognition with OpenCV
Privacy and ethical considerations

Wrap-Up and Next Steps

Review tools, platforms, and datasets
Best practices for edge deployment
Career paths and future trends in Edge AI
Final Q&A and feedback

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants will be evaluated based on:
Daily quizzes, mock questions and query resolution. Participation in hands-on exercises and labs. Performance in the final review and hands-on exercises will be evaluated.
ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

Edge AI for Computer Vision Training Events in saudi-arabia

Online Events

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More Upcoming Session Dates

November 2026

📍 Riyadh, Saudi Arabia

11th Nov 2026→13th Nov 2026

🌐 Online Instructor-Led

11th Nov 2026→13th Nov 2026

📍 Riyadh, Saudi Arabia

25th Nov 2026→27th Nov 2026

🌐 Online Instructor-Led

25th Nov 2026→27th Nov 2026

December 2026

📍 Riyadh, Saudi Arabia

8th Dec 2026→10th Dec 2026

🌐 Online Instructor-Led

8th Dec 2026→10th Dec 2026

📍 Riyadh, Saudi Arabia

19th Dec 2026→21st Dec 2026

🌐 Online Instructor-Led

19th Dec 2026→21st Dec 2026

Events for other courses in Riyadh, Saudi Arabia

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Edge AI for Computer Vision Training in Riyadh