career path · 11 chapters · ~7h 34m

let ai do the grunt work, you do the analysis

the data analyst path teaches you the python to pull data from anywhere, clean it, and turn messy inputs into something you can actually analyze.

who this is for

you work with data, and the boring 80 percent is the part ai should be doing: pulling it, cleaning it, structuring it. you need enough python to build that, and to trust what comes back. this path gets you there.

what you'll be able to do

read data as rows and records in code. pull data from files and from other companies' apis. get clean, structured fields back from an ai model out of messy free text. build small data pipelines, and check the output instead of trusting it.

the route, in order

start in analytics studio with a messy export, trace it back to its source, and turn it into a defensible memo. the shared builder spine supplies the data-shape, model, and evaluation skills that make the analysis reproducible. self-paced; the full route is listed below.

  1. 01analytics studioch 52 · ~1h 1m
  2. 02from worker to builderch 00 · ~1h 14m
  3. 03read the scriptch 01 · ~21m
  4. 04read the data shapesch 02 · ~23m
  5. 05read the failurech 03 · ~24m
  6. 06mutationch 07 · ~10m
  7. 07read the pipelinech 04 · ~26m
  8. 08llm apisch 13 · ~45m
  9. 09structured outputch 14 · ~38m
  10. 10context and retrievalch 22 · ~1h 15m
  11. 11eval-driven ai developmentch 21 · ~57m

how it works

no videos, no fizzbuzz. every step shows a small piece of ai-written code. you read it, predict what it does, find the bug, fix it, run it. it all runs in your browser.

where you end up

builds data pipelines, ai-assisted analysis, structured extraction from messy sources.

free to start, no signup. plus unlocks every chapter at once; the free path moves through them in order. teams get progress visibility and role-fit rollout — see for teams.