“I really enjoyed this course. It explained the fundamentals of text annotation in a simple and easy-to-follow way, making it suitable for beginners. I learned about different text annotation techniques and gained a better understanding of how annotated data is used to train AI models. I would recommend this course to anyone who wants to start a career in data annotation or artificial intelligence.”
Data Annotation Basics
Text Annotation BASICS
Read carefully for AI. Sentiment analysis, topic classification, intent detection, and NER for NLP and chatbots.
Self-Paced
Always Open
Optional Certificate
Part of the Data Annotation Basics programme.
Self-Paced · Always Open
Free
Optional certificate: S$9
Learn at your own pace — no fixed schedule
Structured self-paced course modules
Theory lessons, examples, and knowledge checks
Optional paid certificate (after passing the assessment)
Overview
Start your Text Annotation journey.
Text labeling is where language meets machine learning. The work is reading carefully and deciding: is this review positive or negative, what’s this article about, what is the user actually asking for, which words name a person or a place. Every chatbot, every classifier, every NER pipeline starts with humans annotating text examples — and getting the conventions right matters more than volume.
This Basics course covers the conventions: sentiment analysis, topic classification, intent detection, and named entity recognition (NER). 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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Sentiment Analysis
What sentiment analysis is and how positive, negative, neutral, and mixed labels apply.
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Topic Classification
How topic classification assigns category labels based on subject matter.
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Intent Detection
How intent detection identifies what a user is asking for.
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Named Entity Recognition (NER)
What NER captures: people, places, organisations, and dates in a passage.
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Spotting Correct vs Incorrect Annotations
How to recognise the difference between a clean annotation and a sloppy one.
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.
Success Stories
What our trainees say
Unedited feedback from graduates who completed this course.
“Great course for beginners in Data Annotation!”
“i learnt alot in a short time to progress my learning in data labelling annotation.”
“Its fun and insightful, allows me to have basic understanding of data annotation!”
“I have learned annotation basics, done my assessments and passed. Its perfect!”
“It's perfectly designed for starters!”
Got Questions?
Frequently Asked Questions
Everything you need to know about this course.
It's designed for absolute beginners. No AI knowledge, no coding background, no NLP experience required. Text annotation is also a natural starting point for anyone whose strongest skill is reading carefully (editors, translators, researchers, paralegals).
The course is taught in English and covers conventions that apply across languages. Worth noting as honest market context: being a fluent native speaker of a less-widely-supported language is a real edge in production text annotation. LLM evaluation, multilingual chatbot training, and content moderation in non-English languages all pay premium rates for native annotators because there aren't enough of them.
Self-paced theory lessons and an online knowledge assessment on the e-learning platform. The Basics tier is focused on understanding the conventions: what sentiment, topic classification, intent detection, and named entity recognition 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 Text Labeling 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 text-annotation standards; the paid Text Labeling Essentials course is the hands-on path toward that. 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, segmentation, and 3D point cloud, all at the same level as this one. To go deeper into text annotation specifically, the paid Text 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.
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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