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Analyse One Real Month of Your Business

The capstone project for AI for Data Analysis — a free AI & Emerging Tech course. Pass it and you earn a certificate anyone can verify.

Start the course free Download the project workbook

The project unlocks once you complete the lessons. The workbook is free to download now so you can see exactly what is expected.

What you will submit

A single document (Google Doc, Word file, or pasted text) containing: a description of your cleaned and anonymised dataset, your three analytical questions, the AI's answers, your two-way verification of one key number, one honest chart (pasted or linked), and one clear decision with a short honest summary of the month.

What to do, step by step

  1. Take one real month of your own business records (sales notebook, Opay/Moniepoint export, WhatsApp orders, or Google Form responses) and build ONE clean spreadsheet — rows are records, columns are Date, Product, Quantity, Amount, and Customer. Write 2-3 sentences describing what your dataset contains and how many rows it has.
  2. Before doing anything online, make an 'upload copy' that protects your customers: delete the phone-number column and replace real names with codes like Customer 1, Customer 2. Confirm in one sentence that you anonymised it.
  3. Write THREE sharp analytical questions about this month — each naming what you want, the measure, and the time frame — with at least one being a decision question (something that would change what you restock or who you reward).
  4. Upload the anonymised sheet to an AI tool (or use Google Sheets + Gemini / Excel + Copilot) and run your three questions. Save the AI's answers with the actual naira figures.
  5. Pick the SINGLE most important number from your analysis and verify it two ways — spot-check it by hand AND ask the AI to show its working. Write 2-4 sentences saying exactly what you checked, whether the numbers agreed, and what you found (including if the AI was wrong).
  6. Turn one of your tables into ONE clear, honest chart (right type, titled, axes labelled, value axis starting at zero) and write ONE decision you will actually act on, plus a short honest summary of the month — bad numbers included.

Files to work with

Project workbook (fill in, then submit)The whole brief, an evidence checklist, the grading rubric as a self-check and the link-sharing steps in one file. Opens in Word, Google Docs or WPS.Word · 6 KB

How it is graded

CriterionWeight
Clean, anonymised dataset — data is tidy (consistent dates, plain-number amounts, one fact per column) and customer names/phone numbers are removed or coded before upload20%
Sharp questions — the three questions each name what, the measure, and the time frame, with at least one genuine decision question15%
Verification of one number — a single key figure is checked TWO ways (by hand and by asking the AI to show its working) with a clear, specific note on what was found30%
Honest chart and conclusion — one correctly chosen, clearly labelled chart with a zero-based axis, and a summary that reports the real numbers including the disappointing ones25%
Decision — one concrete, action-shaped decision (restock, drop, reward, open earlier) that follows directly from the verified findings10%

You need 65% overall to pass. A failed submission comes back with feedback and can be revised and resubmitted.

Before you submit: make your link public

If your work lives in Google Drive or Google Docs, open Share → General access and change “Restricted” to “Anyone with the link” (Viewer). Then paste the link into a private browser window: if it opens without sign-in, you are ready. A private link cannot be graded — it is the single most common reason a good project fails.

Frequently asked questions

Do I have to finish AI for Data Analysis before submitting the project?

Yes. The submission screen opens once every lesson in AI for Data Analysis is marked complete. The lessons are where the methods, the Nigerian context and the worked examples the project depends on are taught.

How is the project graded?

An examiner scores each rubric criterion from 0 to 100 and weights them as shown on this page; you need 65% overall to pass. Most submissions are graded within minutes and you get written feedback on what was strong and what to improve.

Can I resubmit if I fail?

Yes. A failed project comes back with feedback; revise the weak parts and resubmit. A passed project is final — the certificate is issued and cannot be re-rolled.

What do I actually submit?

A write-up of what you did (under 5,000 characters). You can mention a public link to supporting files in the write-up. The free project workbook on this page walks you through all 6 steps.

Is the certificate real?

Yes. Passing this project issues a certificate with a unique verification code. Anyone — an employer, a client, a school — can open the verification page and see that the certificate is genuine and which project earned it.

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Ready to earn this certificate?

AI for Data Analysis is free and self-paced. Finish the lessons, complete this project, and the certificate is yours to share.

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