The learning path

Learn the foundations

A practical sequence for developers. Start with context, then follow a value into a row.

01
Clinical trials for developers
Understand the study context before designing the first table or endpoint.
Explain how study, subject, site, visit and observation identities differ.
02
How EDC systems work
Separate collection workflows, recorded values and the exports developers consume.
Trace a collected value without confusing workflow state with data meaning.
03
Introduction to CDISC
Place collection, exchange, tabulation and analysis standards in an engineering workflow.
Identify which standards question belongs to which layer of a data pipeline.
04
Understanding SDTM
Read a domain by asking what one row represents and which context gives its variables meaning.
Distinguish domain, observation class and variable without treating the lesson as a full catalog.
05
Clinical data models
Separate operational entities from observation rows, and make joins deliberate.
Explain how a form-centered representation can differ from a tabular extract.
06
Variables and missingness
Keep identifiers, values, precision and unavailable metadata distinguishable.
Recognize when a convenient data conversion invents information.
07
Controlled terminology
Separate a codelist, a concept and the value a dataset actually carries.
Explain why a familiar label is not enough to establish an allowed output value.
08
From collection to a tabular example
Trace four synthetic observations through a small, inspectable transformation.
Account for every example output value and identify what the transformation does not establish.