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Annotation and quality of training data

Prepare and check the data AI models depend on.

Your running project

A dataset in a local language

The need
Prepare annotated sentences a model can learn from, with measured quality.
The data
Sentences you collect, with people's consent.
External tools
Label StudioTableurKappa de Cohen

Workshop

Establish the needs

Who uses it, what problem it solves, how to tell it worked.

Precision of your question: 0/5

What you will learn

  • Clear, consistent annotation guidelines
  • Annotation tools: text, image, audio
  • Measuring inter-annotator agreement and quality
  • Bias, African languages and personal data

Certifications to aim for at the end

We found no recognised annotation certification, only platform certificates. CDMP covers data management and quality, not annotation itself.

These certifications are issued by their own bodies, not by Nangmo, and their exams are paid for with them. Checked on 3 November 2026: confirm the language, price and exam location on their site before registering. These exams are generally taken without AI: you will need to read and reason on your own.

How to start a career in this field

  1. 1Annotate a small dataset in your language, with written guidelines.
  2. 2Have a second person annotate it and measure your agreement.
  3. 3Publish the dataset and its method: few candidates do.
  4. 4Start with annotation assignments, then aim for a quality reviewer or data project lead role.

First jobs to aim for

  • Data annotator
  • Data quality reviewer
  • Data project lead

The workshop is open, but this path's lessons are not online yet. Tell us you are interested: it helps us decide which to write first.