AIFLX

Library / Artificial Intelligence

Enterprise GenAI with RAG and Agents

On Udemy

About this course

This course contains the use of artificial intelligence.

Enterprise GenAI with RAG and Agents is a practical course designed to help professionals understand how to architect, secure, evaluate, and scale enterprise generative AI applications. The course connects large language models with organizational knowledge, external tools, business systems, governance controls, and production operations.

You will begin by exploring the enterprise GenAI landscape, including the business drivers behind adoption, common architecture patterns, and available deployment models. You will learn how organizations can choose between public cloud, private cloud, hybrid, and on-premises approaches based on data sensitivity, integration needs, cost, control, and scalability.

The course then examines retrieval-augmented generation, commonly known as RAG. You will learn how enterprise documents, databases, policies, knowledge bases, and other trusted information sources can be connected to large language models. Topics include document ingestion, chunking, metadata, embeddings, vector search, retrieval design, ranking, filtering, and response grounding.

You will learn how effective enterprise RAG systems improve accuracy by providing relevant context before an answer is generated. The course also explains citation handling, source traceability, retrieval evaluation, and techniques for reducing hallucinations when the available information is incomplete.

The agentic-workflow section introduces AI agents, planning, tool calling, orchestration, and multi-step automation. You will examine how agents can retrieve information, call APIs, interact with databases, coordinate specialized capabilities, and complete business processes. You will also compare single-agent, multi-agent, and orchestrated workflow patterns.

Enterprise AI requires strong governance and security. You

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