Build Chroma Search
Build Chroma Search is an intermediate, project-based course for developers and aspiring machine learning engineers who want to build and deploy a complete, real-world semantic search application. In today's AI-driven landscape, keyword search is no longer enough; this course teaches you how to leverage the power of vector embeddings and the specialized vector database, Chroma, to create a search engine that understands meaning, not just words.
You will progress through a full development lifecycle, from indexing a document collection to exposing your search functionality through a deployable Flask API. The course places a strong emphasis on professional standards, guiding you to quantitatively measure your API's performance using critical relevance metrics like Mean Reciprocal Rank (MRR) and precision@5. Through hands-on labs and a final summative project, you will not only build a functional search API but also produce an evaluation report to validate its quality, equipping you with a portfolio-ready project and the skills to tackle advanced information retrieval tasks.
Watch on Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: RAG Basics
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
When Should You Use Text2Cypher in a GraphRAG Pipeline
Dev.to AI
How to build a production RAG pipeline in Python (without a vector database)
Dev.to · Ayi NEDJIMI
Architecting Sub-150ms Hybrid RAG for Voice Agents: Combining pgvector, BM25, and Async FastAPI…
Medium · Python
Security Controls in Enterprise RAG: Keys, Audit Logs, and the Hierarchy That Prevents Role Elevation
Dev.to · Manjunath
🎓
Tutor Explanation
DeepCamp AI