What you’ll learn…

As automation accelerates, the most consequential decisions are no longer technical. They arise at the interpretation layer, where data is selected, transformed, reused, and given meaning. Course 1 establishes this foundation, because every later system inherits the assumptions, permissions, and governance decisions made upstream.

Across the full six-part program, you’ll learn how to:

• How to better understand where data originates, how it’s interpreted, and where regulatory exposure is introduced

• Where to apply governance, supervision, and documentation before analytics or AI systems scale

• How to identify misinterpretation, bias, and misuse emerge through ordinary data decisions

• When to design oversight structures that remain defensible as automation increases speed and reach

• How to explain data use in a way regulators can reconstruct, evaluate, and audit

Each lesson includes a downloadable PDF with extended analysis and curated reference materials tied to real regulatory expectations.

By the end of the six courses, you’ll be able to explain, govern, and defend how data is used inside a financial organization (not just how it’s analyzed), so that analytics, automation, and AI can scale while operating within boundaries regulators recognize as credible.