📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of Building RAG Pipelines with LLMs, from foundations to a certified capstone project.
Outline
Explore what Retrieval‑Augmented Generation is and why it matters • Identify core components of a RAG pipeline • Analyze benefits and limitations of RAG architectures
Outline
Generate embeddings using OpenAI and Hugging Face models • Apply chunking and preprocessing strategies for optimal retrieval • Design prompt templates tailored for RAG workflows • Connect LLMs to chosen vector databases
Outline
Implement hybrid search (BM25 + embeddings) for superior recall • Extend RAG to structured and unstructured data sources • Create multi‑turn conversational RAG experiences
Earn government-registered certification in Building RAG Pipelines with LLMs
e-Certificate and e-Marksheet issued on successful completion.
