What You'll Learn
- Identify high-value business use cases for RAG across teams and workflows
- Design a modular, scalable RAG stack for enterprise deployment
- Build a content strategy for sourcing, chunking, and indexing knowledge
- Establish governance practices for access, traceability, and compliance
- Evaluate RAG vendors based on privacy, control, and integration options
- Mitigate risks like hallucination, bias, and data exposure in RAG systems
- Track and report KPIs that measure RAG’s business impact and trust
- Craft a long-term RAG vision aligned with AI agents and automation
Requirements
- No coding or AI development experience required — this course is designed for strategic thinkers, not engineers
- A basic understanding of how your organization uses internal documents, knowledge bases, and workflows
- Familiarity with enterprise tools like SharePoint, Notion, Google Workspace, or CRMs (helpful but not mandatory)
- Ideal for those in management, IT, operations, legal, or innovation roles
- Curiosity and openness to exploring how AI can enhance decision-making and knowledge access across the enterprise
Who This Course is For
- Business and Functional Leaders (e.g., in HR, Legal, Ops, Finance) looking to unlock the value of organizational knowledge through AI
- Enterprise Architects and IT Strategists who want to design and scale RAG infrastructure
- AI and Innovation Officers tasked with operationalizing GenAI in real-world, trustworthy ways
- Data Governance and Compliance Professionals who need to evaluate AI systems for risk, traceability, and accountability
- Team Leads and Product Managers seeking to integrate RAG into workflows, agents, and user-facing apps
- Consultants and Advisors helping organizations plan or pilot RAG-enabled systems
- Tech-Savvy Executives and CIOs who need to understand the business impact, architecture, and evolution of RAG
- AI Enthusiasts and Career Switchers aiming to upskill in applied GenAI strategy and enterprise deployment
Your Instructor
Gourav J. Shah
Premium Instructor | 200,000+ Students | DevOps/AIOps/MLOps
4.4 Instructor Rating
5,018 Reviews
202,458 Students
27 Courses
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