Core AI

RAG & Vector Search

Retrieval-augmented generation, vector databases, embeddings and semantic search

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Skills in this topic
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RAG Basics
beginner
Chunk documents with LangChain or LlamaIndex
Vector Stores
intermediate
Set up Pinecone, Weaviate, or pgvector
RAG Evaluation
intermediate
Run RAGAS evaluation on a RAG pipeline
Advanced RAG
advanced
Build a hybrid BM25 + dense retrieval pipeline
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Embed Everything
📚 External: Coursera ↗
Self-paced
Embed Everything
Opens on Coursera ↗
RAG Systems & Agentic Workflows with Pinecone and LangGraph
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Self-paced
RAG Systems & Agentic Workflows with Pinecone and LangGraph
Opens on Coursera ↗
Building Multimodal Data Pipelines
📚 External: Coursera ↗
Self-paced
Building Multimodal Data Pipelines
Opens on Coursera ↗
Multimodal Retrieval Augmented Generation (RAG) using the Vertex AI Gemini API
📚 External: Coursera ↗
Self-paced
Multimodal Retrieval Augmented Generation (RAG) using the Vertex AI Gemini API
Opens on Coursera ↗
Grasp Vector DB Basics
📚 External: Coursera ↗
Self-paced
Grasp Vector DB Basics
Opens on Coursera ↗
Music as Biology: What We Like to Hear and Why
📚 External: Coursera ↗
Self-paced
Music as Biology: What We Like to Hear and Why
Opens on Coursera ↗