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

Upcoming Sessions

Classroom sessions
Online sessions

Course Introduction

Generative Artificial Intelligence (GenAI) is reshaping how enterprises operate, make strategic decisions, and create value. With the rise of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents, organizations can now automate complex workflows, enhance decision-making, and deliver highly personalized customer experiences. The transformative potential of these technologies is accelerating digital innovation across industries, enabling businesses to stay competitive in an AI-driven economy.

This Enterprise GenAI & AI Agents Training Course offers a practical, business-oriented approach to understanding and deploying GenAI solutions effectively. Participants will explore the architecture, capabilities, and limitations of LLM-powered systems, while learning to design AI agents for real-world business applications. Through hands-on exercises, interactive case studies, and guided implementation roadmaps, professionals will gain the skills to integrate AI solutions into enterprise workflows confidently and responsibly.

Key Highlights of the Course:

  • Explore the fundamentals of Generative AI, LLMs, and AI Agents for business productivity.
  • Learn to design intelligent workflows and automate enterprise processes.
  • Understand Retrieval-Augmented Generation (RAG) frameworks and their applications.
  • Gain practical skills to build and deploy AI agents for real-world use cases.
  • Address governance, ethical considerations, and risk mitigation in enterprise AI.

Objectives

By the end of this Enterprise GenAI & AI Agents Training Course, participants will gain the knowledge and skills to leverage AI technologies strategically. This course empowers professionals to implement AI solutions that drive measurable business impact.

Participants will be able to:

  • Comprehend the core concepts of Generative AI, Large Language Models, and RAG systems.
  • Design AI-driven workflows that enhance operational efficiency and productivity.
  • Evaluate, select, and implement suitable LLM platforms and architectures for business needs.
  • Build practical AI agents and virtual assistants for enterprise applications.
  • Implement retrieval-based AI solutions using structured and unstructured data sources.
  • Assess AI risks, ensure ethical practices, and establish governance frameworks.
  • Develop a strategic AI adoption roadmap aligned with organizational objectives.

Training Methodology

This training course combines modern adult-learning techniques with hands-on, experiential learning to ensure participants gain both theoretical understanding and practical expertise. The course blends instructor-led sessions with interactive exercises, group discussions, and real-world case studies to make learning engaging and impactful.

Participants will work on practical AI tasks, including prompt engineering, designing autonomous agents, and deploying retrieval-augmented solutions. The methodology emphasizes application-driven learning, enabling attendees to translate AI concepts into actionable strategies and solutions within their enterprise. By the end of the course, participants will have a clear understanding of how to implement AI effectively, from planning to deployment, while navigating ethical, governance, and operational considerations.

Who Should Attend?

This Enterprise GenAI & AI Agents Training Course is designed for professionals who want to leverage AI technologies to drive business innovation, efficiency, and growth.

Ideal participants include:

  • Business leaders and executives leading digital transformation initiatives.
  • IT managers, system architects, and technical decision-makers.
  • Data scientists, AI practitioners, and analytics professionals.
  • Innovation, strategy, and product development specialists.
  • Operations and process improvement managers seeking automation solutions.
  • Consultants and technology advisors supporting enterprise AI adoption.

Course Outline

Day 1: 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

Day 2: 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

Day 3: 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

Day 4: 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

Day 5: 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

Providers and Associations

Anderson
Aztech Training
Coventry

Certificate

  • COPEX Certificate of Attendance will be provided to delegates who attend and complete the course

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Related Categories

Digital Transformation Artificial Intelligence (AI)

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