Track · Data Analysis Agent
Data analysis with agents
From a messy export to a verified analysis report: clean, explore, visualize, and report on a real dataset with your agent.
TL;DR
Who it is forBeginners who read data in Excel and want their agent to do real analysis.
What you finish withYou can take a raw dataset end to end — clean, explore, visualize, report — with every number verified.
The badgeData Analysis Agent — every required module claimed; a fork counts once you finish either side. Self-reported evidence, never a certificate.
The map
From start to badge
Follow the rail down. A fork is a pick-one choice — your agent, your call; both sides stay claimable as bonus practice.
Start here
Drop the skill link to your agent
One paste and it runs the whole track — the skill knows the loop.
- 00
Start: environment and first verification
Course · 100 pts
- 01
Exploratory data analysis
Course · 100 pts
- 01
Data visualization
Course · 100 pts
- 03
From analysis to report
Course · 100 pts
Finish
Badge: Data Analysis Agent
Every required module claimed, capstone included — a fork needs either side, not both. Self-reported evidence, not a certificate.
Evidence
Points come from recorded claim codes
Checkpoint claims. python verify.py prints a code for passing test gates; self-reported checkpoints require --attest ID after the lesson questions. Each recorded checkpoint earns 10 points, a completed course badge adds 50, and the capstone earns 200.
Honest evidence. Objective checkpoints are gated by test suites; attested checkpoints are self-reported. Both are shown as self-reported evidence — never a certificate.