3D Point Cloud BASICS
Get oriented in 3D annotation. Cuboid conventions, sensor fusion, and 3D segmentation for autonomous-driving and robotics AI.
Self-Paced · Always Open
Free
Optional certificate: S$9
Overview
Start your 3D Point Cloud journey.
3D point clouds look strange the first time you see one — a cloud of dots in space, often visualised top-down (bird’s-eye view) because it’s the most usable angle. It’s the most technically distinctive annotation modality, and it pays the best of the five at entry level for exactly that reason. Autonomous vehicles, robotics, and mapping all need humans who can think spatially about what a sensor saw.
A quick note on what the data looks like: in this course the point clouds come from ground-mounted sensors on vehicles, visualised top-down. It is not aerial or drone data — the perspective is overhead, but the sensor is on the ground.
This Basics course covers the conventions: 3D bounding boxes (cuboids), sensor fusion with LiDAR, and 3D semantic segmentation. Self-paced theory and knowledge checks; no fixed schedule.
Part of the Data Annotation Basics learning track. Optional verifiable certificate available for a small fee.
What You Get
What's included in your training
Structured Learning Modules
Learn at your own pace through structured modules on the DeeLab Academy learning platform.
Self-Paced Schedule
No fixed schedule. Start when you want, finish at your own pace.
Knowledge Checks
Worked examples and per-unit practice quizzes with instant feedback, plus a final knowledge assessment on the e-learning platform (80% to pass).
Optional Certificate
Optional verifiable certificate available for a small fee after you pass the final assessment.
Outline
What you'll learn
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Point Cloud Basics
How sensors produce point clouds and how the bird's-eye view reads.
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3D Bounding Boxes (cuboids)
What 3D bounding-box annotation is and how cuboids fit objects in space.
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Sensor Fusion (camera + LiDAR)
How sensor fusion cross-references 3D points with synchronised camera images.
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3D Semantic Segmentation
How 3D semantic segmentation assigns a class to each point in the cloud.
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Spotting Correct vs Incorrect 3D Annotations
How to recognise geometry mistakes that break 3D annotation downstream.
Part of the Data Annotation Basics programme.
Self-Paced Course
Free
Optional certificate: S$9
- Full access to the learning environment
- Complete at your own pace
- Professional certification optional
How our free courses work
🌱 One free course at a time — finish this one before you start another.
✍️ When you complete it, a quick rating and honest review are required before your next free course unlocks — the only cost, and how we keep them free.
Frequently Asked Questions
Everything you need to know about this course.
It's designed for beginners. No AI knowledge, no coding, and importantly no prior 3D modelling background required. Point cloud annotation is a new visual literacy you build during the course; the only prerequisite is willingness to think spatially.
No. This is a common point of confusion because point clouds are usually visualised top-down (bird's-eye view, the most usable angle), which can look like aerial data at first. In this course (and in almost all production autonomous-driving and robotics work), the data is captured from ground-mounted sensors on vehicles or robots. The perspective is overhead but the sensor is on the ground.
Self-paced theory lessons and an online knowledge assessment on the e-learning platform. The Basics tier is focused on understanding the conventions of 3D point cloud annotation: 3D bounding boxes (cuboids), sensor fusion with LiDAR, and 3D semantic segmentation. There is no hands-on work with annotation tools in this course; that comes in the paid 3D Point Cloud Essentials course.
The course is free, but the certificate is not — claiming it is optional and costs a small fee. It's verifiable proof that you've completed the self-paced course and passed the online knowledge assessment. Useful on a CV or LinkedIn profile as foundation evidence. It does not mean you've been trained to production 3D annotation standards; the paid 3D Point Cloud Essentials course is the hands-on path. Essentials-level courses make up the Certified Data Annotator (CDA) programme.
Two natural directions from here. To broaden your foundation, the Data Annotation Basics (DAB) programme has free courses on image, video, audio, text, and segmentation, all at the same level as this one. To go deeper into 3D point cloud work specifically, the paid 3D Point Cloud 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.
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.
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