Category: Tutorials
You are in the right place if you want a lesson you can follow, not a glossary and not a product homepage. This shelf holds most of the articles on Analytics Made Simple. Two paths sit inside it on purpose. SQL is the database path: you have rows, and you need to ask a question without exporting another spreadsheet. AI is the tool path: chat products, open-weight models, and the jobs those tools are actually good at. Other tutorials land here when they teach a skill that does not belong on a narrower shelf.
A category page is the pile. A series page is the path, with a place to start and an order. If you open a tag or page 2 of this list, you are in a filing cabinet. The lesson is the article, or the series hub that lines the articles up.
Where to start: if the pain is a table, open the SQL series and use the first part on that page. If the pain is a model name or a chat tool, open the AI category and pick the product you already have on screen. If you are not sure which job you have, open Learn and choose the track that matches the work, not the logo.
When do you need the ChatGPT API instead of a ChatGPT subscription?
A ChatGPT plan is for a person typing; the API is for a program, with its own account and bill. Follow one team-chat bot idea from a free…
What are Claude Design and Claude Science, and who should use them?
Claude Design handles visual work (decks, mockups, prototypes, brand systems, exports). Claude Science is a research workbench with tools, compute, and auditable artifacts, not peer review. Part 4…
How to summarize data with groupby in pandas
Learn pandas groupby as split-apply-combine, the same idea as SQL GROUP BY. Build sum, mean, count, and multi-metric aggregations, with a clear sales-by-region before and after table example.
Which ChatGPT model should you use? A plain-English guide
Pick a ChatGPT model by testing it on your own work. Check for missing facts, a vague request, or the wrong mode before you switch, then run a…
Selecting, filtering, and sorting in pandas
Map SQL SELECT, WHERE, and ORDER BY onto clear pandas patterns you can debug at work. Select columns, filter with boolean masks, sort results, and keep method chains…




