Practical Computer Vision Mastery: 20+ Python & AI Projects
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Practical Computer Vision Mastery: 20+ Python & AI Projects

Muhammad Yaqoob G
4.5(1.4K students)
Self-paced
All Levels

About this course

Unlock the power of image- and video-based AI in 2025 with 20+ real-time projects that guide you from foundational theory to fully functional applications. Designed for engineering and science students, STEM graduates, and professionals switching into AI, this hands-on course equips you with end-to-end computer vision skills to build a standout portfolio.Key Highlights:Environment Setup & Basics: Install Python, configure VS Code, and master OpenCV operations—image I/O, color spaces, resizing, thresholding, filters, morphology, bitwise ops, and histogram equalization.Core & Advanced Techniques: Implement edge detection (Sobel, Canny), contour/corner/keypoint detection, texture analysis, optical flow, object tracking, segmentation, and OCR with Tesseract.Deep Learning Integration: Train and deploy TensorFlow/Keras models (EfficientNet-B0) alongside YOLOv7-tiny and YOLOv8 for robust detection tasks.GUI Development: Build interactive Tkinter interfaces to visualize live video feeds, detection results, and system dashboards.20+ Hands-On Projects Include:Smart Face Attendance with face enrollment, embedding extraction, model training, and GUI integration.Driver Drowsiness Detection using EAR/MAR algorithms and real-time alert dashboards.YOLO Object & Weapon Detection pipelines for live inference and visualization.People Counting & Entry/Exit Tracking with configurable line-coordinate logic.License-Plate & Traffic Sign Recognition leveraging Roboflow annotations and custom model training.Intrusion & PPE Detection for workplace safety monitoring.Accident & Fall Detection with MQTT alert systems.Mask, Emotion, Age/Gender & Hand-Gesture Recognition using custom-trained vision models.Wildlife Identification with EfficientNet-based classification in live streams.Vehicle Speed Tracking using calibration and object motion analysis.By course end, you’ll be able to:Develop, train, and fine-tune deep-learning vision models for diverse real-world tasks.Integrate CV pipelines into intuitive GUIs for live video applications.Execute industry-standard workflows: data annotation, training, evaluation, and deployment.Showcase a portfolio of 20+ complete projects to launch or advance your AI career.Enroll today and start building your first real-time computer vision app!

Skills you'll gain

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Course Information

Level: All Levels

Suitable for learners at this level

Duration: Self-paced

Total course content

Instructor: Muhammad Yaqoob G

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This course includes:

  • 📹Video lectures
  • 📄Downloadable resources
  • 📱Mobile & desktop access
  • 🎓Certificate of completion
  • ♾️Lifetime access
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