OCI Digital Assistant Professional study plan

Map the Digital Assistant design lifecycle from skill creation through versioning and publishing

Create a new digital assistant and a custom skill, then configure the primary language and invocation name

Define five intents with at least four example utterances each, and annotate entities in those utterances

Explain how the confidence threshold and intent resolution affect routing in a dialog flow

Build a dialog flow with at least three states, including a user-input state, a condition branch, and an entity-resolution state

Configure entity types, including a custom entity list and a composite bag entity for a multi-slot form

Write Apache FreeMarker expressions to read and set context variables inside states

Add a system intent fallback and an unresolved-intent path with a meaningful reprompt

Integrate a REST backend as a custom component, defining the endpoint, authentication, and response schema

Create a custom component with input and output properties and invoke it from a dialog state

Handle backend errors and timeouts with an error transition and a user-facing message

Use a service-level variable to pass session context into the backend call

Implement intent disambiguation when confidence scores are close, using a clarification prompt

Add a multi-turn flow with slot filling and validation for a date and a numeric range

Write a unit test for a custom component using sample payloads and assert on the output properties

Document the data contract between the dialog flow and the backend for two integration points

Configure a web channel and a messaging channel, and compare their session and rendering behavior

Set up channel-specific security, including authentication and allowed origins or webhook verification

Create an environment-specific configuration for a test versus production deployment

Explain how skill versioning and publishing affect live channels

Configure role-based access and separate designer, tester, and viewer responsibilities

Implement logging and analytics review to identify the three lowest-confidence intents in a test conversation set

Harden the assistant by masking sensitive data in logs and limiting backend credentials to a service account

Describe the backup and export strategy for skills and digital assistants

Assemble an end-to-end assistant that covers at least six intents, two backend integrations, and two channels

Run a regression pass over all transcript test cases and fix the top three defects

Tune intent training by adding utterances for the weakest intents and re-measure confidence

Prepare a deployment plan with rollback steps and version pinning

Take two timed practice exams and review every missed question by domain

Re-explain the design lifecycle, dialog flow constructs, custom component contract, and channel security from memory

Close knowledge gaps by rebuilding one weak area in a sandbox assistant

Finalize a one-page exam-day reference of key terms and configuration steps