AI course for your role · 14 chapters · ~10h 3m

Data Analyst

Clean source data, build repeatable analyses, and trace findings back to the evidence.

who this is for

For the data analyst on your team. Assign this course to people responsible for this work, whether they are new to AI or already use it. They build a shared foundation, practice in their role studio, and learn the tools needed to clean source data, build repeatable analyses, and trace findings back to the evidence.

what you'll be able to do

Practice how to clean source data, build repeatable analyses, and trace findings back to the evidence. Build work you can explain to a colleague, with checks and a clear point for human review.

your course, in learning order

start with the map, then the early reading labs so names and values are not a surprise. then the data chapters: dataframes, sql, and dataset pipelines — the python to pull, clean, and check a real table. then analytics studio: trace a messy export back to its source and turn it into a defensible memo. later chapters add the model and evaluation skills that make the analysis reproducible. self-paced; the full route is listed below. Chapters are numbered in the order you take them in this course.

  1. 1. Foundations

    Shared AI foundations and the prerequisites for this role.

    01from worker to builder~1h 45m
  2. 02read the script~21m
  3. 03read the data shapes~23m
  4. 04read the failure~24m
  5. 05mutation~10m
  6. 06read the pipeline~26m
  7. 07dataframes for analysis~43m
  8. 08sql for real tables~28m
  9. 09dataset formats, ingestion, and validation pipelines~37m
  10. 2. Role practice

    Practice the work of a data analyst in the role studio.

    10analytics studio~1h 1m
  11. 3. Applied skills

    Build on the studio with tools, workflows, and checks for your role.

    11llm apis~45m
  12. 12structured output~38m
  13. 13context and retrieval: feeding the model real data~1h 25m
  14. 14test the analysis before you cite it~57m

how it works

Learn through interactive exercises in your browser. Start with the foundations, then work through practice for your role. Many later exercises ask you to read, edit, and run code; the introductory lessons help you get started without prior coding experience. You can skip a stuck exercise and continue reading.

where you end up

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

training a team? assign this course to the people doing this role, then review their work together. plan your team’s training.

One lesson is free in the browser. Plus includes curriculum access, saved progress, sync, and completion certificates for $12/month or $99/year. Team training is $297 per seat each month and stays sales-led.