Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity

The Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity Course gives technology, data, and business transformation professionals a comprehensive, technically grounded understanding of enterprise generative AI — covering Large Language Model architecture, prompt engineering, Retrieval-Augmented Generation systems, AI agent design, and the governance and implementation frameworks needed to deploy GenAI at enterprise scale.

Generative AI is moving rapidly from experimentation to enterprise deployment, and the organisations that benefit most are those whose professionals understand how LLMs actually work, how to engineer reliable prompts, how RAG systems reduce hallucinations, and how AI agents can be designed to autonomously complete complex business tasks. That depth of capability is what this course builds.

Across five focused days, delegates progress from LLM fundamentals and prompt engineering through RAG architecture, vector databases, multi-agent systems, and enterprise deployment, culminating in a practical AI agent build and an enterprise AI adoption roadmap. Every day includes hands-on application to ensure learning translates directly into practitioner-level capability.

The Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity Course is built for professionals who want to move beyond using GenAI tools and develop the depth of understanding to design, build, and govern enterprise AI systems that deliver real, measurable productivity outcomes.

The Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity Course is designed to develop comprehensive enterprise GenAI capability, from LLM fundamentals and prompt engineering through RAG systems, AI agent design, and enterprise deployment governance.

By the end of this course, participants will be able to:

• Explain how Large Language Models work including transformers, tokens, and embeddings and evaluate popular LLM platforms and architectures
• Identify LLM limitations including hallucinations and reliability challenges and evaluate their implications for enterprise deployment
• Apply prompt engineering principles to design structured prompts that improve accuracy, control, and business task performance
• Automate workflows using GenAI tools and build productivity assistants across marketing, finance, operations, and HR functions
• Explain RAG architecture and apply data ingestion, knowledge base preparation, and vector database principles to enterprise knowledge assistant development
• Reduce hallucinations and improve accuracy in enterprise AI systems using RAG design techniques
• Explain how AI agents work, evaluate agent frameworks and orchestration tools, and design autonomous task agents
• Design multi-agent collaboration systems and build a working business AI agent in a practical workshop
• Apply enterprise system integration, security, privacy, and compliance considerations to GenAI deployment
• Develop an enterprise AI governance framework and adoption roadmap with ROI measurement and risk mitigation strategies

The Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity Course is designed for technology, data, and business transformation professionals who are building, evaluating, or governing enterprise GenAI and AI agent solutions.

This course is suitable for:

• AI engineers and data scientists designing and deploying LLM, RAG, and AI agent systems for enterprise use
• Technology leads and solution architects evaluating GenAI platform options and enterprise integration strategies
• Digital transformation professionals driving GenAI adoption across business functions and workflow automation
• Product managers developing AI-powered products that leverage LLM, RAG, or agent capabilities
• IT and cybersecurity professionals managing security, privacy, and compliance in enterprise GenAI deployments
• Business analysts and operations professionals applying prompt engineering and GenAI automation to productivity improvement
• AI governance and risk professionals developing frameworks for responsible enterprise GenAI deployment
• Graduate technology and data professionals entering enterprise AI roles requiring LLM, RAG, and agent expertise

The Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity Course is delivered through a technically structured, progressively building learning approach that moves from LLM foundations and prompt engineering through RAG system design, AI agent development, and enterprise deployment governance. Each day builds directly on the previous, ensuring delegates develop an integrated, end-to-end understanding of enterprise GenAI architecture and deployment.

Hands-on sessions including prompt design exercises, a RAG system walkthrough, and a practical AI agent build are integrated throughout, culminating in an enterprise AI adoption roadmap session.

Delivery methods include:

• Instructor-led sessions covering LLM architecture, prompt engineering, RAG design, agent frameworks, and governance principles
• LLM platform evaluation sessions examining popular architectures, capabilities, limitations, and enterprise suitability
• Prompt engineering workshops designing structured prompts for accuracy, consistency, and business task automation across multiple functions
• Practical AI agent build developing a working business AI agent in a structured hands-on workshop
• Enterprise deployment and governance sessions applying integration, security, compliance, ROI measurement, and AI adoption roadmap development

• AZTech Certificate of Completion for delegates who attend and complete the training course