Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
16 Hour(s) 29 Minute(s)
Language
English
Rating
Course Overview
Build Real-World Computer Vision Projects using YOLOv7 YOLOv8 YOLOv9 YOLOv10 YOLO11 YOLO26: Detection, Tracking, AI Apps
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!
Course Content
- 30 section(s)
- 208 lecture(s)
- Section 1 Introduction
- Section 2 How to run your first YOLOv7/YOLOv8 Deep Learning program in < 10 minutes
- Section 3 A comprehensive overview of YOLO
- Section 4 Understanding Deep Learning
- Section 5 Understanding YOLOv7 & YOLOv8
- Section 6 Tools Installation (Windows)
- Section 7 Dataset Preparation
- Section 8 YOLOv7, YOLOv8, YOLOv9, and YOLOv10 prerequisites Installation (Windows)
- Section 9 YOLOv7 Installation (Windows, Google Colab)
- Section 10 YOLOv8 Installation (Windows, Google Colab)
- Section 11 Perform Object Detection using YOLOv7 pretrained model on image, video, webcam.
- Section 12 Perform Object Detection using YOLOv8 pretrained model on image, video, webcam.
- Section 13 Training YOLOv7 detection model on custom dataset
- Section 14 Training YOLOv8 detection model on custom dataset
- Section 15 YOLOv7 & YOLOv8 Performance Measurement
- Section 16 YOLOv7 New Features
- Section 17 YOLOv8 New Features
- Section 18 Training YOLOv8 Classification model on custom dataset (Real-World Project #2)
- Section 19 Training YOLOv8 Segmentation model on custom dataset (Real-World Project #3)
- Section 20 Real-World Project 4 : Squat Counter
- Section 21 YOLOv9 Object Detection
- Section 22 YOLOv10 Object Detection
- Section 23 YOLO11 Object Detection
- Section 24 YOLO11 Instance Segmentation
- Section 25 YOLO11 Image Classification
- Section 26 YOLO11 Pose Estimation
- Section 27 YOLOv11 Oriented Bounding Boxes (OBB)
- Section 28 YOLO26 Fundamentals
- Section 29 YOLO26 Object Detection
- Section 30 YOLO26 Instance Segmentation
What You’ll Learn
- How to run, from scratch, a YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLOv11 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
Reviews
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MMuhammad Iqbal R
Amazing, Beautiful
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LLoh Swee Kuan
the content is good but the training time is abit long. overall is good
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AAlexandr Krassavin
The teacher just reads text from slides, did not tell any explanation of concepts "Why? For What? Bussines cases, etc"
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BBrent Jericho Uyguangco
Yes, this is a very great straightforward course.
