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

Scan 40 real job listings and map skill demand

Do the analysis every career counsellor wishes existed: collect 40+ real, current internship/job listings for one role, use AI to structure the mess into a dataset, and map what the market actually wants.

Data AnalysisSpreadsheet AnalysisData VisualisationSQL & DatabasesAnalytical Reasoning

Posted by The AI Internships

The work brief

  1. 01Pick one role you might want (data analyst, digital marketer, web developer).
  2. 02Collect 40+ current listings from LinkedIn, Indeed, company career pages, or a trusted local job board into a structured CSV: title, company, location, requested skills, pay or stipend when listed, and requested experience.
  3. 03Use AI to normalise the messy skill names ("MS Excel" = "Excel"), then count what appears most — and spot-check its merges; "Java" is not "JavaScript".
  4. 04Report: top 10 skills, pay ranges by location when available, and the 3 most surprising findings — with a chart.

What you’ll produce

4 deliverables

Submission standard

Submit the role, your 40+ row listings CSV, your findings, and a chart. Listings must be real and current — we spot-check companies. Include your AI workflow — tools, best prompts, and what you changed. Include a dated screenshot of your job-board search results and add the listing URL for each row so companies and postings are checkable.

  • The role you scanned

    Short answerRequired

  • Your listings dataset as CSV (40+ rows: title, company, location, skills, pay if listed)

    40+ rows (title, company, location, skills, pay if listed) with a source/listing-URL column per row so each posting is checkable.

    CSV dataRequired

  • Top skills, available pay ranges, and your 3 most surprising findings

    Written responseRequired

  • A chart of skill demand (or pay by location)

    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.

  • Dated screenshot of your real job-board search results (showing the platform, the role query, and the date)

    Show the actual LinkedIn/Indeed results page with the date and result count — proves listings are current and real.

    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.

Dataset quality

29%

40+ real, current listings with consistent structured columns.

Findings

29%

Counts and ranges follow from the CSV; surprises are genuinely non-obvious.

Chart

14%

The chart accurately shows the demand pattern.

Real, current listings

29%

The dated results screenshot and per-row source links must show these are real, currently-posted listings matching the CSV. Invented companies/rows or no dated evidence 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.