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

Building Intelligent AI Systems for Enterprise Transformation

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Why Choose Us

The Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity training course develops the technical understanding required to design, build and govern enterprise AI systems. It is intended for technology, data and business transformation professionals seeking to progress beyond simply using generative AI tools. Key subjects include Large Language Model architecture, prompt engineering, Retrieval-Augmented Generation, AI agent design, and frameworks for governance and enterprise-scale implementation. These capabilities help practitioners understand how LLMs operate and how generative AI can produce measurable productivity outcomes.

Over five focused days, delegates advance from LLM fundamentals and reliable prompt design to RAG architecture, vector databases, multi-agent systems and enterprise deployment. They examine how RAG systems can reduce hallucinations and how AI agents can autonomously perform complex business tasks. Hands-on application takes place each day, translating technical knowledge into practical, practitioner-level capability. The course concludes with the practical construction of an AI agent and the creation of an enterprise AI adoption roadmap.

This Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity training course will highlight:

  • Understanding Large Language Model architecture and operation
  • Engineering reliable prompts for enterprise applications
  • Designing RAG systems that reduce hallucinations
  • Applying vector databases within RAG architecture
  • Developing AI agents and multi-agent systems for complex business tasks
  • Planning governed enterprise deployment through an AI adoption roadmap
Why Choose Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity
Course Goals

What are the Goals?

The Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity Course aims to build comprehensive enterprise GenAI capabilities, covering everything from LLM foundations and prompt engineering to RAG systems, AI agent design, and governance for enterprise deployment.

Upon completing this course, participants will be able to:

  • Describe how Large Language Models operate, including transformers, tokens, and embeddings, and assess widely used LLM platforms and architectures
  • Recognise LLM limitations, including hallucinations and reliability issues, and assess their impact on enterprise deployment
  • Use prompt engineering principles to create structured prompts that enhance accuracy, control, and performance in business tasks
  • Use GenAI tools to automate workflows and develop productivity assistants for marketing, finance, operations, and HR functions
  • Describe RAG architecture and use data ingestion, knowledge base preparation, and vector database principles to develop enterprise knowledge assistants
  • Use RAG design techniques to minimise hallucinations and enhance accuracy in enterprise AI systems
  • Describe how AI agents operate, assess agent frameworks and orchestration tools, and create autonomous task agents
  • Create multi-agent collaboration systems and develop a functional business AI agent during a practical workshop
  • Apply considerations relating to enterprise system integration, security, privacy, and compliance when deploying GenAI
  • Create an enterprise AI governance framework and adoption roadmap incorporating ROI measurement and risk mitigation strategies

Who is this Training Course for?

This Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity training course is designed for:

  • AI and Machine Learning Engineers
  • Generative AI Specialists
  • Data Scientists
  • Software Engineers
  • Solutions Architects
  • Enterprise Architects
  • Prompt Engineers
  • Business Analysts
  • IT Managers
  • Digital Transformation Managers
  • Intelligent Automation Specialists
  • Innovation Managers
Learning Approach

How will this Training Course be Presented?

The Enterprise GenAI & AI Agents: Mastering LLM and RAG for Productivity Course uses a technically organised, progressive learning methodology, advancing from LLM fundamentals and prompt engineering to RAG system design, AI agent creation, and enterprise deployment governance. Every day builds directly upon the preceding one, enabling delegates to gain an integrated, end-to-end understanding of enterprise GenAI architecture and deployment.

Practical sessions are incorporated throughout, including prompt design exercises, a walkthrough of a RAG system, and a hands-on AI agent build, concluding with an enterprise AI adoption roadmap session.

Delivery approaches include:

  • Instructor-led training addressing LLM architecture, prompt engineering, RAG design, agent frameworks, and governance principles
  • LLM platform assessment sessions exploring widely used architectures, capabilities, limitations, and suitability for enterprise use
  • Prompt engineering workshops creating structured prompts to support accuracy, consistency, and business task automation across multiple functions
  • A practical AI agent build focused on developing a functional business AI agent through a structured hands-on workshop
  • Enterprise deployment and governance sessions covering the application of integration, security, compliance, ROI measurement, and AI adoption roadmap development

The Course Content

Foundations of Generative AI & LLM Ecosystems

  • Overview of AI evolution and generative AI landscape
  • How Large Language Models work (transformers, tokens, embeddings)
  • Popular LLM platforms and architectures
  • Business use cases across industries
  • Limitations, hallucinations, and reliability challenges

Prompt Engineering & Productivity Automation

  • Principles of prompt engineering for business tasks
  • Designing structured prompts for accuracy and control
  • Automating workflows using GenAI tools
  • Building productivity assistants for teams
  • Case studies: marketing, finance, operations, HR 

Retrieval-Augmented Generation (RAG) Systems

  • Understanding RAG architecture and components
  • Data ingestion and knowledge base preparation
  • Vector databases and semantic search
  • Building enterprise knowledge assistants
  • Improving accuracy and reducing hallucinations 

AI Agents for Business Applications

  • What are AI agents and how they work
  • Agent frameworks and orchestration tools
  • Designing autonomous task agents
  • Multi-agent collaboration systems
  • Practical workshop: building a business AI agent 

Deployment, Governance & Implementation Strategy

  • Integrating AI into enterprise systems
  • Security, privacy, and compliance considerations
  • AI governance frameworks and risk mitigation
  • Measuring ROI and performance of AI solutions
  • Developing an enterprise AI adoption roadmap
Recognition

Certificate

  • • Wallstreet Development Academy Certificate of Completion for delegates who attend and complete the training course.

Frequently Asked Questions

This course covers enterprise generative AI, AI agents, large language models, and retrieval-augmented generation. It focuses on how these technologies contribute to intelligent AI systems. The overall context is improving productivity and supporting enterprise transformation.
The course addresses large language models as a core part of enterprise generative AI systems. It places LLMs alongside AI agents and retrieval-augmented generation rather than treating them as an isolated topic. The emphasis is on their relevance to intelligent systems for enterprise productivity and transformation.
Yes, AI agents are a central subject of the course. They are covered in relation to generative AI, large language models, and retrieval-augmented generation. The enterprise focus connects these technologies with productivity and organisational transformation.
The training aims to build understanding of generative AI, AI agents, large language models, and retrieval-augmented generation. It develops the learner’s ability to relate these technologies to intelligent enterprise systems. The stated direction is applying that knowledge to productivity and enterprise transformation.
You will learn about the core technologies named in the course: generative AI, AI agents, large language models, and retrieval-augmented generation. The course connects these areas to the development of intelligent enterprise AI systems. It also considers their role in productivity and transformation.
Retrieval-augmented generation, or RAG, is presented as a key element of enterprise AI system development. The course connects RAG with large language models and AI agents. Its treatment is framed around building intelligent systems that support enterprise productivity.
The course focuses on using GenAI, AI agents, LLMs, and RAG in the context of enterprise productivity. It examines these technologies as components of intelligent AI systems. The course title specifically links mastery of these areas with productivity improvement.
This course is relevant to people seeking to understand enterprise applications of GenAI, AI agents, LLMs, and RAG. Its subject matter suits learners interested in intelligent AI systems, productivity, and enterprise transformation. The provided course information does not specify particular job roles or prerequisites.

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