PRACTICE LABS
·100% Synthetic · HIPAA SafeLearn by doing — in working labs.
Hands-on environments with synthetic patients you can't break. Every lab runs at your level: a guided visual mode for beginners, a pro mode when you're ready.
Choose Any 6 Free Practice Labs
0 of 6 Selected (6 Left)Hand-pick any 6 practice workbenches from our 34-lab catalog to unlock permanently for free.
Workbench Directory
Data Foundations — start here
Core data representations, conversion, and version control for clinical systems.
Data Formats Playground
No jargon, no code, no login. See one blood-pressure reading written as plain English, then as CSV, JSON and XML — then check your own files in a live inspector that explains every error in ordinary words.
API Playground
How one piece of software asks another for something — explained with no code and no login. Dissect a real request piece by piece, then drive a live practice API that makes you meet 401s, rate limits, pagination and duplicate-payment bugs on purpose.
Version Control Playground
Git and GitHub explained with no command line and no login — repo, commit, branch, pull request, merge, deploy. Follow one change to a clinical rule from edit to live, and learn what to do when someone commits an API key or patient data by mistake.
Interoperability & Integration
HL7 v2, FHIR R4, and translation pipelines across healthcare environments.
FHIR Conformance & Profiling
The rigorous 'structured FHIR' skill employers test: how a StructureDefinition constrains a base resource into a profile (US Core, India's NDHM IG), binding strength, must-support, slicing, and whether an instance actually conforms. Eight graded conformance scenarios.
Universal Modern Healthcare Data Lifecycle
The complete enterprise health data lifecycle: multi-source ingestion, AI-assisted semantic crosswalks, longitudinal OMOP/FHIR lakehouse modeling, and clinical LLM hallucination guardrails.
Clinical Systems & Workflow
Care plans, medication administration, and computerized provider order entry.
EHR Workflow · CPOE & Order Safety
The clinician-facing layer: place orders on a synthetic patient and watch a real check engine fire allergy, drug–drug interaction, renal and duplicate-therapy alerts as you type. Plus order sets and the workflow judgement — wrong-patient entry, alert fatigue, and closing the administration loop.
Nursing Informatics · Care Plans, eMAR & NEWS2
The administration end of the medication loop, where CPOE hands over. Build a care plan from an assessment, run barcode medication administration against a real five-rights engine on a ward where two patients share a surname, and score a quietly deteriorating patient with the real NEWS2 table.
Simulation & Digital Twins
Physiological mathematical models and virtual patient calibration.
Digital Twin · Physiological Simulation
A real glucose–insulin model running in your browser. Calibrate insulin sensitivity until the twin reproduces this synthetic patient's actual CGM curve — then ask it what-if questions. The difference between a generic simulation and a twin is the calibration.
Imaging Informatics · DICOM
Medical imaging, PACS routing, and DICOM standards.
Imaging Informatics · DICOM & PACS
The imaging half of health IT: decode a DICOM header tag by tag, build DICOMweb (QIDO/WADO/STOW) requests, trace the Patient›Study›Series›Instance model, and walk the radiology workflow from order to report. Synthetic data, no PHI.
India Health Stack · ABDM
Ayushman Bharat Digital Mission, ABHA, and consent managers.
ABDM · India Health Stack
Work the consent flow that powers India's health data exchange — HIP, HIU, Consent Manager and Gateway — plus ABHA identity, the ABDM building blocks, and the NDHM FHIR Implementation Guide. The India-native skill no global platform teaches.
Terminology & Coding
SNOMED CT, LOINC, and clinical concept hierarchies.
ICD-10-CM Clinical Coding
Decode the anatomy of real ICD-10-CM codes (category, laterality, 7th character, placeholder X), then code synthetic cases — the engine validates billability and specificity, not multiple choice.
ICD-11 Post-coordination
ICD-10 is a book that was digitised; ICD-11 is a web service. Learn the skill that cannot be taught from an index — composing a code from a stem plus extension codes, and reading a cluster string the way a terminology server does.
Clinical NLP & AI
Named entity recognition and clinical language models.
Clinical AI/ML · Evaluate & Govern
Prove you can judge a clinical model, not just run one: move a decision threshold and watch the confusion matrix, ROC/AUROC and calibration respond; audit fairness across subgroups; write a model card; and rule on EU AI Act, drift and human-oversight scenarios. Synthetic cohort.
Revenue Cycle & Medical Coding
Medical billing, claim scrubbing, and remittance processing.
RCM Workbench
The all-in-one revenue-cycle environment: scrub claims before submission, work denials by CARC/RARC reason code, and decode X12 835 remittances — with coding-QA and eligibility tools landing next. One robust RCM technology lab, not a single trick.
Security, Audit & Compliance
Healthcare regulatory frameworks and security audits.
Audit & Compliance Workbench
The governance skill set of the AI-native era: review a synthetic ePHI access log for violations, rule on HIPAA/DPDP compliance scenarios, and audit an AI agent's decisions, plus a breach-notification calculator and a Safe Harbor de-identification tool. Five tools, one workbench. Synthetic data, no real PHI.
Healthcare Data Quality & Governance Studio
Profile datasets, resolve patient chart duplicates via Master Patient Index (MPI), enforce Kahn/OMOP clinical plausibility rules, and generate institutional data quality scorecards.
Data Science & Research
Biostatistics, epidemiology, and observational health data.
Health Data Analytics Lab
Write real SQL against a synthetic patient dataset. Query across 5 tables — patients, encounters, diagnoses, vitals, and lab results — to answer clinical questions. Guided mode scaffolds the query; Pro mode is a blank editor.
Health Data Science Lab
Write Python with pandas and matplotlib against a synthetic 20-patient hospital dataset — all running in your browser via WebAssembly. Five scenarios from demographics to length-of-stay analysis. Guided mode provides starter code; Pro mode is a blank slate.
Biostatistics Lab
Analyse a synthetic randomized controlled trial with Python, scipy and statsmodels — running in your browser. Five scenarios: descriptive statistics, the independent t-test, chi-square, correlation & linear regression, and Kaplan-Meier survival analysis. Guided mode provides starter code; Pro mode is a blank slate.
Epidemiology & EBM Lab
Turn study data into evidence with Python — running in your browser. Five scenarios: disease frequency, measures of association (RR / OR / NNT), diagnostic-test evaluation (sensitivity, specificity, ROC/AUC), confounding & Mantel-Haenszel adjustment, and an evidence-based-medicine appraisal (ARR / RRR / NNT with confidence intervals).
Data Harmonization · OMOP CDM
Harmonize messy source data into the OMOP Common Data Model — the foundation of real-world-evidence and pharma research. Map local codes to standard concepts, build a patient cohort, run drug–condition queries, and compute prevalence across standard concepts. Synthetic data only; the CDM structure is open.
Pharmacovigilance · MedDRA
Detect drug-safety signals with Python on a synthetic spontaneous-reporting database. Navigate the MedDRA hierarchy (PT → SOC), code and roll up adverse events, and compute disproportionality (PRR / ROR) with the classic signal criteria. Synthetic MedDRA codes only — the dictionary is licensed.
Healthcare Data Quality & Governance Studio
Profile datasets, resolve patient chart duplicates via Master Patient Index (MPI), enforce Kahn/OMOP clinical plausibility rules, and generate institutional data quality scorecards.
Universal Modern Healthcare Data Lifecycle
The complete enterprise health data lifecycle: multi-source ingestion, AI-assisted semantic crosswalks, longitudinal OMOP/FHIR lakehouse modeling, and clinical LLM hallucination guardrails.
Computational Life Sciences & Bioinstrumentation
Sequence analysis, biostatistics, epidemiology, and biomedical signal processing for biotech & engineering learners.
Bioinformatics Lab
Work with DNA and protein sequences in Python — GC content, reverse complement, transcription and translation, FASTA parsing and pairwise alignment — entirely in the browser. Built for biotech, life-sciences and bioinformatics students.
Bioinstrumentation Lab
Process biomedical signals in Python with scipy.signal: generate and filter a synthetic ECG, detect heartbeats, and analyse the frequency spectrum with the FFT. Built for biomedical-engineering students.