Image Annotation BASICS

It's designed for absolute beginners. No prior AI knowledge, no coding, no annotation background required. If you've never labelled data before, this is the natural place to start. It also works as orientation for project managers, QA leads, and anyone who works alongside annotation teams and wants to understand what the work actually involves.

Image labelling typically means drawing a rectangle (a bounding box) around an object and assigning a class. Image segmentation means drawing the exact pixel-level outline. Labelling is faster, more universal, and where almost everyone starts. Segmentation is slower, more precise, and the foundation for medical and autonomous-driving work. If you're new, start here; the Image Segmentation Basics course is the natural next step.

Self-paced theory lessons and an online knowledge assessment on the e-learning platform. The Basics tier is focused on understanding the conventions: what bounding boxes, classification, multi-label tagging, and attribute annotation are for, and how to recognise a clean annotation from a sloppy one. There is no hands-on work with annotation tools in this course; that comes in the paid Image Labeling Essentials course.

The course is free, but the certificate is not — claiming it is optional and costs a small fee. It's a verifiable confirmation that you've completed the self-paced course and passed the online knowledge assessment. Useful as proof of foundation knowledge on a CV or LinkedIn profile. It is honest about its scope: it does not mean you've been trained to production-annotator standards. That's what the paid Image Labeling Essentials course is for. Essentials-level courses make up the Certified Data Annotator (CDA) programme.

Three paths from here. To broaden your foundation, the Data Annotation Basics (DAB) programme has free courses on video, audio, text, segmentation, and 3D point cloud, all at the same level as this one. To go deeper into image labeling specifically, the paid Image Labeling Essentials course is the next level up: online sessions with an industry trainer, access to the labeling tools used in production, ongoing support, and a graded final assessment. The Essentials-level courses make up the Certified Data Annotator (CDA) programme. Separately, we run the Object Recognition Bootcamp (ORB): a 4-week cohort with intensive learning-by-doing on real data. ORB is its own track with its own bootcamp certification; the requirements match (and in places exceed) the equivalent CDA course, but the two tracks don't share credentials. Pick what fits how you learn best.

You have three months to complete the course, counted from the end date of your first course run. The deadline is fixed and doesn't reset if you move to a later run.

Yes — you're automatically enrolled in the run you choose, and you can move to another scheduled run of the same course up to twice from your dashboard. Your payment carries over and your completion deadline stays pinned to your first run's end date.