About the Course
Generative AI and Large Language Models (LLMs) dramatically reduce documentation overhead while multiplying analytical depth and speed. This course teaches business analysts how to leverage AI to extract structured requirements from raw meeting notes, generate comprehensive PRDs and user stories, and uncover hidden edge cases.
Participants also practice Diagram-as-Code workflows using Mermaid.js and PlantUML, AI-assisted data exploration, and enterprise data privacy guardrails.
Target Audience and Prerequisites
- Business analysts and systems analysts looking to accelerate analysis and documentation with AI tools
- Product Owners, product managers, and project leads aiming to improve requirement completeness
- Foundational business analysis knowledge is sufficient; no prior coding or AI background is required
Key Takeaways
- Prompt Engineering for BAs: Craft role-, context-, and constraint-driven prompts for high-precision analysis outputs
- Automated Specification: Transform raw stakeholder transcripts into structured
BRDs,PRDs, user stories, andGherkincriteria - Diagram-as-Code Generation: Generate editable
MermaidandPlantUMLprocess and sequence diagrams in seconds - Quality and Edge-Case Auditing: Use LLMs to detect requirement ambiguities, conflicting rules, and missing NFRs
Curriculum
Generative AI Fundamentals and Prompt Engineering for BAs
- How
LLMswork and mapping high-impact AI use cases across the business analysis lifecycle - BA prompt engineering patterns:
Few-Shot,Chain-of-Thought, persona framing, and structured output templates - Enterprise data privacy, PII anonymization, and mitigating model hallucinations
AI-Assisted Elicitation and PRD / User Story Authoring
- Preparing stakeholder interviews, simulating user personas, and mining requirements from meeting transcripts
- Decomposing product visions into epics,
INVESTuser stories, andBDD/Gherkinacceptance criteria - Drafting, restructuring, and summarizing
BRDandPRDdocuments against enterprise templates
Diagram-as-Code and Technical Systems Analysis with AI
- Generating
Mermaid.jsandPlantUMLcode for process flows,Sequence,State, andERDdiagrams - Deriving decision tables, sample
JSONAPI payloads, and synthetic test datasets from business rules - Reverse-engineering business logic from legacy documentation, schemas, or UI screenshots
Requirement Quality Auditing, Edge-Case Discovery, and Custom BA Copilots
- Auditing requirement specifications for ambiguity, contradictions, and missing
NFRsusing critique prompts - Systematically discovering negative scenarios, failure modes, and complex
edge cases - Designing reusable custom GPTs and AI agent workflows tailored to team analysis standards
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