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Micro-internship brief ≈7h in one sittinglow-code

Tell a data story from a real public dataset

Governments and public bodies publish mountains of open data — most of it never gets read. Pick a real public dataset, ask one sharp question, and answer it with AI-assisted analysis — a one-page data story with 3 charts.

Data AnalysisSpreadsheet AnalysisData VisualisationAnalytical Reasoning

Posted by The AI Internships

The work brief

  1. 01Find a dataset on your country or local open-data portal, Kaggle, the World Bank, or another public source about something you care about (education, transport, prices, sports).
  2. 02Ask ONE specific question the data can answer (e.g. "which districts improved school enrolment fastest?").
  3. 03Use AI + a spreadsheet (or Python) to explore, clean, and answer it — then verify the three numbers your story leans on against the raw data.
  4. 04Write the story: the question, the answer, 3 charts, and what the data CAN’T tell you.

What you’ll produce

4 deliverables

Submission standard

Submit the dataset link, your question, the full story, and a chart image. The story must cite specific numbers from the dataset. Include your AI workflow — tools, best prompts, and what you changed. Attach a screenshot of the actual dataset rows containing the figures your story quotes.

  • Link to the public dataset you used

    Link to the public dataset — must open so a grader can trace your figures back to it.

    Public linkRequired

  • The one question your story answers

    Short answerRequired

  • Your data story: answer, evidence, limitations (cite real numbers)

    Cite exact figures using the dataset's own column/field names so each number is traceable to the linked source.

    Written responseRequired

  • Your best chart from the story

    Image uploadRequired

You’ll complete these inside your private workspace.

What you must submit as proof

This brief requires evidence an AI can’t fabricate.

  • Screenshot of the dataset (the actual rows/table you used) showing the figures your story cites

    Show the real dataset view with the numbers you quote, so the story can be traced to the source.

    Image uploadRequired

Submissions without this evidence cannot be submitted.

Protect other people in your proof. Blur faces, names, phone numbers and email addresses before you upload, and refer to anyone you worked with by role or number ("Listener 1", "the stall owner"). Your proof is only ever used to check your work — it is never published, never appears on your certificate, and is never shown in your public portfolio.

How your work is evaluated

The passing benchmark is 70/100.

Question sharpness

14%

A specific, answerable question — not a topic.

Story & evidence

29%

The answer cites real numbers from the linked dataset and admits limitations.

Visualisation

29%

The chart is honest (labelled axes, sensible scale) and supports the story.

Numbers trace to the dataset

29%

The specific figures in the story must be locatable in the linked dataset and its screenshot. Invented or untraceable numbers, even in a polished story, are a fail.

How we grade your AI usage

30% of your score

Using AI is the point — it’s the skill this certificate proves. You’ll answer three short questions about how you used it: what you asked, what was wrong with its first answer, and what you changed. Specific, honest answers score high. “I pasted the brief and submitted the answer” scores near zero.