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YOLOv11 : Complete Machine Learning Project For Experts
Rating: 4.5 out of 5(35 ratings)
4,357 students

YOLOv11 : Complete Machine Learning Project For Experts

YOLOv11 : Complete Machine Learning Project From Scratch || Yolov11 Machine Learning Project || ML Project
Created byARUNNACHALAM SHANMUGARAAJAN
Last updated 5/2025
English
English [Auto],

What you'll learn

  • Dataset Preparation
  • Model Training and Testing
  • YOLOv11 Basics
  • Complete Project Implementation

Course content

2 sections • 9 lectures • 31m total length

  • Introduction To Project0:34

    Learn to create and annotate a dataset for a YOLO v11 project, then train the dataset using YOLO v11 across two modules.

  • Project Class 1 : Project Workspace Creation1:49

    Sign up on Roboflow, create a new project named Home intrusion detection, select object detection, choose a license, and define the intrusion class.

  • Project Class 2 : Dataset Collection4:16

    Build a home intrusion detection image dataset by gathering relevant images from Google and Roboflow, organize them into a folder, and aim for 1000+ images before annotation.

  • Project Class 3 : Dataset Annotation4:30

    Learn to annotate datasets using manual labeling in Roboflow, applying bounding boxes, polygons, and smart polygon tools to create intrusion detection labels and split data for training, validation, and testing.

  • Project Class 4 : Dataset Download2:25

    Download and prepare the dataset from Roboflow by creating a new version, applying preprocessing and augmentation, downloading in YOLO v11, then extract and review train, test, valid and data.yaml.

Requirements

  • Basic Python Knowledge

Description

Unlock the full potential of machine learning with the "YOLOv11: Complete Machine Learning Project From Scratch" course! This course is an in-depth, hands-on guide designed to lead you step-by-step through building a real-world project using YOLOv11, the latest advancement in the YOLO (You Only Look Once) family of object detection models. Starting from the absolute basics, this course equips you with the essential skills and practical knowledge to create a sophisticated object detection system from scratch. You’ll explore everything from setting up your environment to implementing a fully functional machine learning model.

With a focus on practical learning, this course covers all aspects of working with YOLOv11, including dataset preparation, model training, and evaluation. You'll gain experience with data annotation, model fine-tuning, and how to handle common challenges in object detection. By the end of this course, you’ll know how to deploy your model, enabling it to make predictions in real-time, suitable for applications in security, automation, and more.


  • Fundamentals of YOLOv11: Learn how YOLOv11 outperforms previous versions with enhanced accuracy and speed, and understand its key components.

  • Project Setup & Dataset Preparation: Set up your development environment, collect and annotate data, and prepare a training-ready dataset.

  • Model Training and Evaluation: Master the training process for YOLOv11, learning how to optimize performance and evaluate results accurately.

  • Deployment Techniques: Implement your trained model for real-time object detection applications.

Perfect for students, developers, and AI enthusiasts, this course is tailored to those who want to build robust skills in machine learning. Start your journey to creating high-impact AI models today by enrolling in the "YOLOv11: Complete Machine Learning Project From Scratch"!

Who this course is for:

  • Students and Professionals in ML
  • Tech Enthusiasts and Hobbyists

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