SQL + Data
Turn operational ambiguity into answerable questions: schemas, joins, analysis, validation, and the discipline to know when the data does not support the conclusion.
Solutions Lab
I wanted the training to behave more like the work.
So I built a 32-week healthcare solutions apprenticeship that combines hands-on technical work with a living simulation. I still have to write the SQL, work with APIs, reason through architecture, and understand the data — but the environment can also change while I work. New evidence appears. Assumptions break. Stakeholders disagree. Deadlines move. I have to decide what the evidence actually supports.
Enter the interactive lab ↗ View the evidence on GitHub ↗Python + APIs
Move from describing an integration to building one: backend fundamentals, automation, service boundaries, and reliable exchange between systems.
Healthcare Data
FHIR, HL7, interoperability, clinical workflows, and the gap between a standard on paper and what survives inside a real health system.
Cloud + Architecture
State, databases, permissions, failure handling, deployment, security boundaries, and the tradeoffs that appear once a prototype becomes infrastructure.
AI Systems
Evaluation, tool use, human review, simulation, model behavior, bounded execution, and designing around uncertainty instead of hiding it.
Implementation
Requirements, UAT, go-live, adoption, measurement, and the final question that matters: did the system actually change the work?