Learning paths

CluedIn learning paths are role-based, hands-on routes through the platform. They are designed to help you learn how to solve realistic problems in CluedIn rather than repeat feature documentation.

How learning paths work

Product documentation is the authoritative source for how CluedIn features work. Learning paths do not repeat those instructions.

Each module follows the same pattern:

  1. Learning outcome – what you should be able to do.
  2. Scenario – the problem you are solving.
  3. Read – the product documentation you need before starting.
  4. Exercise – the work to perform in a non-production CluedIn environment.
  5. Deliverable – the evidence you should produce.
  6. Complete when – observable criteria for finishing the module.

Use the links in Read for product steps, screenshots, configuration details, and reference information. Use the learning path to understand why and when to apply those features.

Available courses

Course principles

  • Work through the modules in order on the first pass.
  • Practice in a development, test, sandbox, or other non-production environment.
  • Use a realistic dataset that you are allowed to change.
  • Keep evidence from each exercise so later modules can build on earlier work.
  • Treat role boundaries as part of the training: Data Stewards investigate and operate data-quality workflows; Data Architects shape the model, mappings, identity, rules, automation, and downstream behavior.
  • Follow the linked product documentation whenever the learning path and your current CluedIn version differ.

Table of contents