Learn to build intelligent, retrieval-powered AI systems using LangChain, LlamaIndex, and real-world RAG workflows
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Instruction is structured around dedicated hands-on labs within every major section to complement video lectures.
The curriculum moves beyond basic pipelines to include hybrid search, multi-modal RAG, and agentic workflows.
One signal suggests that core RAG explanations may be repeated across multiple sections, such as in the later stages of the course.
A learner signal indicates that practical examples may rely heavily on ChatGPT-based scenarios rather than diverse datasets.
The curriculum aligns with the stated goals of developers and data scientists through its focus on Python-sased RAG pipelines.