Your cart is empty.
Keep shoppingYOLO26 & The Legacy : 6 in 1 YOLO Masterclass 2026
6,242 students
YOLO26 & The Legacy : 6 in 1 YOLO Masterclass 2026
Build Real-World Computer Vision Projects using YOLOv7 YOLOv8 YOLOv9 YOLOv10 YOLO11 YOLO26: Detection, Tracking, AI Apps
Last updated 3/2026
English
What you'll learn
- How to run, from scratch, a YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLOv11 and YOLO26 program to detect 80 object classes in < 10 minutes
- How to install and train YOLOv7 YOLOv8 YOLOv9 YOLOv10 YOLO11 YOLO26 using Custom Dataset & perform Object Detection for image, video & Real-Time using Webcam
- Custom Object Detection, Instance Segmentation, Pose Estimation, Image Classification, Object Tracking + Real-World Projects
- Build 12 Real Projects: Vehicle Counter & Speed Estimation Web App, Suspicious Movement Detection + Telegram Notification, Smart Car Parking Lot System and more
- YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLO11, and YOLO26 architecture and how it really works
- How to find dataset
- Data annotation/labeling
- Automatic Dataset splitting
- How to train YOLO v7, YOLO v8, YOLO v9, YOLO v10, YOLO11, YOLO26 using custom dataset, transfer learning and resume training.
- How to visualize training performance using TensorBoard
- Easily understand The Fundametal Theory of Deep Learning and How exactly Convolutional Neural Networks Work
- Real-World Project #1: Robust mask detector using YOLOv7 and YOLOv8
- Real-World Project #2: Weather Image/Video Classification using YOLOv8
- Real-World Project #3: Coffee Leaf Diseases Segmentation using YOLOv8
- Real-World Project #4: Squat Counter based on YOLOv7 Pose Estimation
- Real World Project #5: Various Vehicle Counter and Speed Estimation Web App with Cool Dashboard using YOLOv9 + Streamlit
- Real World Project #6: Cattle Counter using YOLOv10 + Bytetrack
- Real World Project #7: Person Counter using YOLO11 + Bytetrack
- Real World Project #8: Pothole Segmentation Project using YOLO11
- Real World Project #9: X-Ray Image Classification using YOLO11
- Real World Project #10: Bicep Curl Counter using YOLO11
- Real World Project #11: Car Parking Lot Project using YOLOv11 OBB
- Real World Project #12: YOLO26 Suspicious Movement Detection and Telegram Notification
Explore related topics
Course content
30 sections • 208 lectures • 16h 29m total length
Requirements
- Programming experience is an advantage but not required
- Windows laptop/PC, especially with Nvidia GPU
Description
Want to build powerful AI systems that understand images and video?
In this course, you will master YOLO (You Only Look Once), one of the most popular object detection frameworks in Computer Vision and Deep Learning.
Learn how to build real AI applications using YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLOv11, and the latest YOLO26 (6 in 1 course). Train custom models, detect objects in real time, and run your systems on images, videos, and live webcams.
Everything is explained clearly and step-by-step, making it beginner-friendly.
What You’ll Be Able to Do
By following the tutorial, at the end of this course, you will be able to:
Run YOLO models from scratch and detect 80+ objects in minutes
Train your own models using custom datasets
Build real-time AI systems using webcam and video
Create real-world computer vision applications
Learn Only What Matters
You’ll understand the essentials without getting overwhelmed:
How YOLO evolved into the fastest detection system today
Core deep learning and CNN concepts (explained simply)
How every YOLO architectures actually work
Hands-On Skills You’ll Master
Dataset collection and annotation (LabelImg)
Automatic dataset splitting
Training with custom data and transfer learning
Monitoring performance with TensorBoard
Object detection, Instance segmentation, Object tracking, and Image classification
12 Real-World Projects That Make You Stand Out
These are not toy examples.
These are portfolio-ready systems you can showcase or monetize:
• Vehicle Counter & Speed Estimation Dashboard
• Smart Parking Detection System
• Suspicious Movement Detection with Telegram Alerts
• X-Ray Image Classification (Medical AI)
• Fitness AI: Squat Counter
• Pothole Segmentation for Smart Cities
Plus many more hands-on projects to strengthen your Computer Vision portfolio.
Why This Course Is Different
Covers 6 YOLO versions in one course
Focus on real applications, not just theory
Designed for portfolio, freelance, and job-ready skills
Beginner-friendly but powerful enough for advanced learners
If you want to master YOLO and build real AI vision systems, this course will guide you step-by-step.
Start building your own AI-powered Computer Vision applications today. Enroll now!
Who this course is for:
- Professionals who want to quickly grasp and apply YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLO11 and YOLo26 on real projects
- Undergraduate/Graduate students who are taking computer vision using deep learning as their final project
- Early adopter who is interested in learning Deep Learning and How to Apply it in solving Computer Vision problem