daBongo LMS AI Training Courses

← Back to Course

Enterprise AI Readiness – Data, Workflow, and Deployment Choices

Lesson 2: Data, Documents, and Context

Lesson Objectives

By the end of this lesson, students should be able to:

  • Identify available, missing, stale, and restricted information.
  • Explain why context quality affects output quality.
  • Create a small test set.

Lesson Content

AI systems need usable information. For a simple prompt, the information may be instructions and examples. For a search-and-answer workflow, the information may be documents. For a classification workflow, the information may be labeled examples.

Readiness questions:

  • Is the information current?
  • Is it organized enough to retrieve?
  • Is it written for the audience the AI must support?
  • Does it include edge cases?
  • Are there privacy, permission, or policy limits?
  • Can a person verify the result?

Students should create a test set before launch. A test set is a small group of examples that includes normal cases, hard cases, and cases where the AI should refuse or ask for more information.

Enroll to continue this lesson.

The preview above shows the lesson objectives and opening lesson content. Enroll to view the full lesson, complete the practice work, and take the lesson quiz.

Log In / Create Account Back to Course

← Back to Course