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COURSE OVERVIEW

IT0035 : Face Detection with OpenCV in Python
Face Detection with OpenCV in Python
OVERVIEW
COURSE TITLE : IT0035 : Face Detection with OpenCV in Python
COURSE DATE : May 25 - May 29 2025
DURATION : 5 Days
INSTRUCTOR : Mr. Abdel Aziz Issa
VENUE : Dubai, UAE
COURSE FEE : $ 5500
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Course Description

This practical and highly-interactive course includes real-life case studies and exercises where participants will be engaged in a series of interactive small groups and class workshops. 
 
This course is designed to provide participants with a detailed and up-to-date overview of Face Detection with OpenCV in Python. It covers the face detection and the difference between detection and recognition; setting-up OpenCV in Python and image processing fundamentals in OpenCV; the OpenCV basics for face detection and video capture and processing in OpenCV; the Haar cascade, working with XML Haar cascade files and how OpenCV uses Haar features for face detection, strengths and limitations of Haar cascade; and accessing OpenCV’s built-in Haar cascade XML files, detecting faces in a static image, drawing bounding boxes around detected faces and tuning detection parameters for better accuracy. 
 
Further, the course will also discuss the real-time face detection using Haar cascades, detecting facial features using Haar cascade and performance optimization in Haar-based face detection; the limitations of Haar cascades in face detection and deep learning for face detection; installing and loading OpenCV’s DNN face detector and real-time face detection with deep learning models; the facial landmarks and feature detection and comparing different face detection techniques; and the face tracking with OpenCV and AI-based face detection using deep learning models. 
 
 
During this interactive course, participants will learn the face detection in low-resolution and noisy images, face detection with mask and occlusions and AI-based real-time face detection optimization; using face detection for real-time security monitoring and AI-based intruder detection with face recognition; the facial feature extraction for biometric security and face detection models in smart CCTV systems; the face detection in attendance and access control systems and cloud and mobile applications; and the ethical and privacy concerns in face detection. 

link to course overview PDF

TRAINING METHODOLOGY

This interactive training course includes the following training methodologies:

Lectures
Practical Workshops & Work Presentations
Hands-on Practical Exercises & Case Studies
Simulators (Hardware & Software) & Videos

In an unlikely event, the course instructor may modify the above training methodology for technical reasons.

VIRTUAL TRAINING (IF APPLICABLE)

If this course is delivered online as a Virtual Training, the following limitations will be applicable:

Certificates : Only soft copy certificates will be issued
Training Materials : Only soft copy materials will be issued
Training Methodology : 80% theory, 20% practical
Training Program : 4 hours per day, from 09:30 to 13:30

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