All micro-internships
Micro-internship brief ≈10h in one sittingbuilder

Full EDA in a real notebook — code, charts, narrative

Graduate from spreadsheets: do a complete exploratory data analysis in a Google Colab notebook — pandas for the wrangling, matplotlib for the charts, markdown cells for the story. AI can write code with you, but every cell must run and you must be able to explain it.

Data AnalysisSpreadsheet AnalysisData VisualisationPython for DataAnalytical Reasoning

Posted by The AI Internships

The work brief

  1. 01Pick a real dataset with 200+ rows (Kaggle, data.gov.in, or data you collected in earlier missions).
  2. 02In Colab: load, inspect, clean (show the mess you found), and explore — distributions, group comparisons, at least 3 charts. Write the pandas with AI, but run and understand every cell yourself.
  3. 03Write the narrative in markdown cells as you go: question → what the cell shows → so what.
  4. 04Run the whole notebook top-to-bottom cleanly ("Restart and run all"), then share it with a public link.

What you’ll produce

4 deliverables

Submission standard

Submit the dataset link, the public notebook link (must be viewable without login), your summary of findings, and your favourite chart. We check that cells ran in order. Make sure the shared notebook shows in-order execution counts, and optionally link the AI chat behind your two code fixes.

  • Link to the dataset you analysed

    Public linkRequired

  • Public link to your Colab notebook (viewable without login)

    Public Colab link (viewable without login); cells must show sequential execution counts from a clean top-to-bottom run.

    Public linkRequired

  • Your findings summary — and 2 pieces of AI-written code you had to fix or change, and why

    Findings summary plus the 2 pieces of AI-written code you had to fix or change and why — these fixes must actually appear in the notebook.

    Written responseRequired

  • Your favourite chart from the notebook

    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.

  • Public share link to the AI chat where you wrote/debugged the notebook code

    Optional but rewarded: shows the real code back-and-forth behind the two fixes you describe.

    Public linkOptional

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.

Complete, running EDA

29%

The notebook covers load→clean→explore with 3+ charts and ran top-to-bottom.

Narrative quality

14%

Markdown cells tell the question→evidence→so-what story.

Code ownership

29%

The AI-fix examples show they understood and corrected the code.

Ran-in-order + real fixes

29%

The notebook must show sequential execution counts (a clean top-to-bottom run) and the two described AI-code fixes must be real and present in the notebook. Out-of-order or empty cells, or fabricated 'fixes', 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.