Udemy - Develop a Real-World Vision Security AI Agent from Scratc...

Category : Other
Type: Tutorials
Language: English
Total Size: 1.1 GB
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Last checked: Aug. 8th '26
Date uploaded: Aug. 8th '26
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About Udemy - Develop a Real-World Vision Security AI Agent from Scratc...

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Develop a Real-World Vision Security AI Agent from Scratch https://WebToolTip.com Published 8/2026 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 40m | Size: 1.12 GB Connect local LLMs via LangChain to live webcams. Implement motion tracking with OpenCV and object detection with YOLO What you'll learn Agent Architecture: Master the principles of Simple Reflex Agents and understand how to design software based on a strict Perception-Action loop. Ollama

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Develop a Real-World Vision Security AI Agent from Scratch

https://WebToolTip.com

Published 8/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 40m | Size: 1.12 GB

Connect local LLMs via LangChain to live webcams. Implement motion tracking with OpenCV and object detection with YOLO

What you'll learn
Agent Architecture: Master the principles of Simple Reflex Agents and understand how to design software based on a strict Perception-Action loop.
Ollama Integration: Master local LLM deployment, prompting, and structured data handling inside Python scripts for private, cost-free AI reasoning.
Advanced Python Automation: Write clean, modular, and reusable code by splitting complex core orchestration loops from utility-based pipelines.
State & Cooldown Management: Implement system throttling & cooldown thresholds to ensure your agent manages resources intelligently without spamming actions.
Real-Time Computer Vision: Clean up image streams, process frames using contours, and analyze pixel matrices efficiently.

Requirements
Basic-to-intermediate familiarity with Python programming (loops, variables, functions).
Ollama installed locally (we will guide you through this process!).
No prior experience with complex AI agent architecture or computer vision required—we build up step-by-step!
A built-in webcam or an external camera feed for testing the live perception loop (simulated video files can also be used).