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Build a Private AI Knowledge Base with RAG
New
39 students

Build a Private AI Knowledge Base with RAG

Turn trusted company documents into grounded AI answers through retrieval design, testing, governance, and adoption
Created byDr. Law Payne
Last updated 10/2026
English
English [Auto],

What you'll learn

  • Explain how retrieval-augmented generation grounds business answers in approved documents.
  • Prepare source documents, metadata, permissions, and a maintainable knowledge architecture.
  • Design retrieval and answer workflows with citations, abstention, and human review.
  • Test answer accuracy and relevance, then govern access, updates, and deployment.

Course content

3 sections • 17 lectures • 1h 49m total length

  • How RAG Creates Grounded Business Answers9:54

    This lecture explains retrieval and generation, source authority, business question, citation discipline, system boundary. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

  • Prepare Documents and Knowledge Architecture10:30

    This lecture explains content inventory, source quality, metadata, chunking logic, update ownership. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

  • Design Retrieval and Answer Workflows10:25

    This lecture explains query intent, search strategy, context assembly, answer contract, fallback behavior. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

  • Test Accuracy Relevance and Trust10:31

    This lecture explains evaluation set, retrieval quality, answer quality, hallucination review, user feedback. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

  • Deploy Govern and Improve the Knowledge System10:13

    This lecture explains access control, content lifecycle, usage analytics, change adoption, roadmap. Students apply the ideas to a realistic business decision, examine common failure modes, and complete a practical exercise they can use immediately.

Requirements

  • No coding experience is required.
  • A willingness to apply the frameworks to a real or realistic business situation.
  • Access to common productivity software is helpful but not required.

Description

This course contains the use of artificial intelligence.


Build a Private AI Knowledge Base with RAG gives professionals a structured system to design a grounded AI knowledge system that retrieves useful evidence and produces answers people can verify.


The course is designed for business owners, consultants, knowledge managers, operations leaders, analysts, educators, and product professionals. It moves beyond disconnected tips and tool demonstrations. Students learn how to define the business decision, organize evidence, design a practical workflow, evaluate quality, preserve human accountability, and connect activity to measurable results.


The continuing case follows a multi-location organization where policies, procedures, product knowledge, and client guidance live across outdated documents and disconnected drives. Every lecture includes a management framework, application guidance, quality controls, and an assignment learners can use in an organization, client engagement, career, or business.


Dr. Law Payne combines doctoral-level leadership education with substantial entrepreneurial, marketing, and teaching experience. He holds a Doctor of Business Administration specializing in Organizational Leadership and Development, a master’s degree in Educational Psychology, a master’s degree in Business, and a bachelor’s degree in Business Administration and Marketing. His professional experience includes nine-figure entrepreneurship, published work reaching more than one million copies, and growth leadership involving more than one billion dollars in managed sales.

Who this course is for:

  • Business owners, consultants, knowledge managers, operations leaders, analysts, educators, and product professionals.
  • Professionals who want business value and responsible implementation rather than surface-level hype.
  • Professionals who want a structured, evidence-based approach instead of disconnected tips or tool demonstrations.
  • Leaders and learners who want to preserve human accountability while using artificial intelligence.

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