Microsoft Excel Essentials
Build a solid, reliable foundation in Excel: structure, formulas, formatting and the habits that prevent broken spreadsheets.
Use AI assistants for analysis, documentation and drafting — with the verification habits that keep you safe.
AI assistants are genuinely useful for analytical work: explaining an inherited formula, drafting documentation, suggesting a transformation approach, converting a vague request into a specification. They are also confidently wrong on a regular basis. This course covers both sides honestly.
7 modules · 27 lessons · approximately 4 hours of video
A practical mental model, without hype. Where they are strong, where they are unreliable.
Context, constraints, examples and output format. Iterating instead of accepting the first answer.
Explaining an inherited formula, documenting a workbook, and proposing a clean-up plan.
Excel formulas, DAX measures and M steps — and the test you run before shipping any of them.
Cross-checking totals, edge cases, and the habit of never pasting an unverified calculation into a live model.
What not to paste into a public tool, and how to write a simple internal usage rule.
A frank list of tasks where AI helps, tasks where it wastes time, and tasks where it is dangerous.
Build a solid, reliable foundation in Excel: structure, formulas, formatting and the habits that prevent broken spreadsheets.
Dynamic arrays, advanced lookups, financial and statistical functions, and models that are built to be audited.
Stop cleaning the same file every month. Build repeatable transformations that refresh with one click.