Master Retrieval Augmented Generation & Data Pipelines

About this course

Ready to make AI systems work with your organization’s unique knowledge and data? Most AI implementations fail because they cannot effectively access and process enterprise information. This course helps you overcome that challenge by mastering data pipelines, gen AI and retrieval-augmented generation (RAG) systems that connect AI models with real-world data.

You will learn what retrieval augmented generation (RAG) is and how retrieval augmented generation works, while building systems that transform raw enterprise data into intelligent, context-aware responses. This course turns you into an AI engineer capable of designing scalable RAG pipelines and advanced AI automation workflows.

You’ll master data pipeline engineering, including data warehouse pipeline design, document processing, and transforming unstructured data into AI-ready formats. You will also explore data pipeline vs warehouse concepts and understand the meaning of data pipeline in enterprise AI systems.

This comprehensive program provides a practical approach to retrieval augmented generation systems, covering RAG architecture, embeddings, vector databases, and intelligent retrieval strategies. You’ll also learn what a RAG pipeline is, what RAG is in GenAI, and how to implement RAG AI systems for real-world applications.

Through hands-on labs, you will build production-ready retrieval augmented generation software with adaptive orchestration, personalization, and monitoring. You’ll explore agentic AI workflows and understand what RAG agents are, enabling intelligent and scalable knowledge systems.

You will also gain expertise in:

• Desig

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