Climate Data with AI
Climate professionals are drowning in data. Emissions inventories, finance spreadsheets, NDC trackers, satellite feeds. The problem has never been finding data — it's turning it into something you can defend and communicate. This course teaches you to do that work with AI handling the mechanics while you handle the judgment.
Start course →What you'll leave with
- ✓Identify and evaluate credible climate data sources — and spot the weak ones
- ✓Clean messy real-world data without introducing new errors
- ✓Find the hero metric: the one number that carries your argument
- ✓Build visualizations that are both honest and persuasive under scrutiny
Course sections
Where Climate Data Actually Lives
OWID, IEA, EPA, national inventories, satellite datasets. How to evaluate a source before you trust it — methodology transparency, update frequency, political independence.
Cleaning Data with AI
Raw climate data is always messy. Unit inconsistencies, missing values, aggregation errors, definitional drift. How to use AI as a cleaning assistant without trusting it blindly.
The Hero Metric
One number that tells the whole story. Why dashboards with 47 metrics communicate nothing, and how to find the single metric that actually changes minds.
Honest Visualization
Chart Critique QuizTruncated axes, cherry-picked baselines, misleading color scales. How to design charts that are both honest and persuasive — with a chart critique exercise.
The Data Pipeline
Hero Metric FinderConnect data source → cleaning → analysis → hero metric → visualization into a repeatable pipeline. The Ground Truth Document as anchor. Build your own hero metric.