Who is this data analytics course for?
It is for people who are handed exports and asked for a monthly summary: sales coordinators, finance and operations staff, marketing executives, office managers and small business owners. If you can sort and filter a spreadsheet, you are ready.
Who is it not for?
It is not for people aiming to become data analysts through intensive full-time technical training. The optional Code lessons introduce SQL and Python from zero, but you will not learn data warehousing or dashboard development, and there is no job guarantee. If you want job-ready depth, look for a college analytics programme or a bootcamp with portfolio projects. This course is the practical layer for people who analyse data as part of another job.
What will I learn in this data analytics course?
Each module takes one stage of a real spreadsheet job and pairs a spreadsheet skill with an AI assist and a check.
1. Getting data into shape
Duplicates, blank rows, inconsistent names and dates, and asking AI for cleaning steps or formulas you then test.
2. Summarising with formulas and pivot tables
Totals, averages, counts and pivot tables, with AI explaining or writing formulas you verify on a sample.
3. Comparing periods and groups
Month on month, year on year, percentage change and why small groups produce big swings.
4. Charts that make the point
Choosing between bar, line and table, labelling clearly and avoiding charts that exaggerate.
5. Telling the story
A three-sentence summary, the one chart that matters and recommendations separated from findings.
6. Checking the numbers
Reconciling totals, spot-checking rows and catching AI arithmetic or formula errors before anyone sees them.
How does the personalised path adapt to me?
The diagnostic asks which spreadsheet tool you use, whether it has a built-in AI assistant such as Copilot in Excel, and how confident you are with formulas and pivot tables. A finance assistant who already uses pivot tables jumps ahead to storytelling; a newer marketing executive spends longer on cleaning and formulas. Worked examples use data shaped like your role's, such as invoices, campaign results or stock levels.
What do I practise?
You work on realistic made-up spreadsheets, never your company's confidential data. Each task is marked against a rubric you can read first, feedback is specific, and any score can be flagged for review.
Example task: a fictional four-branch garden centre business, Fernleigh, exports a month of till data with branch names spelt three ways and some refunds recorded as positive sales. You clean the data, build a pivot table of sales by branch and category, and ask an AI assistant to describe the main changes. The rubric checks that branch names are unified, refunds are treated correctly, your total reconciles to the export and you corrected one AI claim that did not match the pivot table.
How long does the data analytics course take?
Lessons take 10 to 15 minutes, short enough to fit around a reporting deadline. The path length depends on your diagnostic and pace, so we do not promise a number of hours. Confident spreadsheet users often finish sooner.
Is there a certificate?
Yes. The final practical assessment gives you a raw export and asks for a cleaned, checked one-page summary with a chart. Passing earns a recognised certificate. It is not an accredited qualification.
How much does it cost?
The course is included in every plan. On Individual you pay USD 79 a month or USD 790 a year. On Team you pay USD 189 a month or USD 1,890 a year for up to 3 members, adding members at USD 49 a month or USD 490 a year, and 25 or more members get volume pricing. Start with a 7-day free trial, and no credit card is needed.