Bolashak Fellows at Johns Hopkins SAIS · Two-Day Seminar 2026

AI & Machine Learning for Governance & Policy Research

Trees, forests, and neural networks on governance data; dictionaries and large language models on Federal Reserve, IMF, and World Bank documents. Everything runs in claude.ai — no installation, no code.

Upload the data Ask in plain English Interpret the output Verify every claim
Start Day 1 → Browse the datasets
Where to go

Four workspaces for the seminar

Each opens in its own page. The datasets and documents are yours to download; the Day 1 and Day 2 pages put ready-to-run prompts next to a link into Claude.

23
DATA

Quality of Government datasets

Twenty-three country-year datasets built from the University of Gothenburg's QoG data — each with a one-click data and description download.

Open datasets →
32
TEXT

Policy documents

Central bank statements, IMF and World Bank reports, rating actions, and communiqués — the raw material for the Day 2 text-analysis labs.

Open documents →
1
MACHINE LEARNING

Day 1 agenda & slides

Prediction on governance data: decision trees, random forests, and neural networks. Full schedule plus every Day 1 slide deck to download.

Open Day 1 →
2
AI & POLICY TEXT

Day 2 agenda & slides

Turning documents into data: dictionary sentiment and large language models on real Fed, IMF, and World Bank text. Schedule plus all Day 2 decks.

Open Day 2 →
HANDS-ON

Labs for Day 1 & 2

The working space: copy a ready-made prompt, open Claude in a new tab, run it on your file, then interpret and verify the result.

Open the labs →
2 days9:00–12:00 & 1:00–5:00
1 toolclaude.ai, free tier
0 codeupload, ask, interpret, verify