Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Data Annotation Master Class 2026
Role Play
Rating: 4.1 out of 5(23 ratings)
140 students

Data Annotation Master Class 2026

Master Data Annotation from Scratch with Hands On Projects – Image, Video & LiDAR Annotation
Created byMohammad Rahish
Last updated 8/2026
English

What you'll learn

  • Master the fundamentals of data annotation, including image, video, and LiDAR data labeling techniques used in real-world AI projects.
  • Learn to create high-quality annotations using bounding boxes, semantic segmentation, polygons, and keypoints with industry standards.
  • Understand and apply Image Segmentation techniques
  • Gain hands-on experience with real datasets and annotation tools used in AI and machine learning workflows.

Course content

7 sections • 21 lectures • 3h 53m total length

  • Welcome Video1:20

    Learn data annotation for ai and computer vision, labeling images, videos, lidar point clouds, and 3d cuboids with tasks like image classification, object detections, semantic and instant segmentations.

  • What is Data Annotation11:07
  • Data Annotation Quiz
  • Course Roadmap6:55

Requirements

  • No prior experience required – this course is designed for complete beginners.
  • Basic computer knowledge (using a mouse, keyboard, and internet browsing)
  • A laptop/PC with internet access (GPU recommended but not required)
  • Willingness to learn and practice with real-world datasets.

Description

Start your journey into Artificial Intelligence without needing any coding skills. This Data Annotation Masterclass is designed to help you understand how AI models are trained using real-world data and how you can become a skilled data annotator.

In this course, you will learn image annotation techniques such as bounding boxes, polygons, and keypoints. You will also explore video annotation, including object tracking and frame-by-frame labeling. Advanced topics like semantic segmentation and LiDAR annotation are covered to give you industry-relevant skills. You will work with tools like CVAT and Label Studio and understand quality metrics such as precision, recall, and accuracy.

This course is fully practical, allowing you to work on real datasets and follow workflows used in AI companies. In addition to technical skills, you will learn how to build a portfolio, prepare a resume, and apply for data annotation jobs or start freelancing.

Whether you are a beginner, student, or professional looking to transition into AI, this course provides a clear and structured path. By the end, you will be ready to contribute to AI projects and begin your career in data annotation. You will also gain confidence in to handling real tasks and understanding clients requirements effectively.

Who this course is for:

  • Anyone curious about how AI models are trained using real-world data.
  • Anyone who wants hands-on experience building production-style AI projects.
  • Students and freshers looking for job-ready skills in machine learning support roles.
  • Freelancers who want to earn through data labeling and annotation projects.

Report abuse