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Build Chroma Search

This course is part of Chroma, Weaviate & Production RAG Deployment Specialization

Instructor: LearningMate

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Build and evaluate a semantic search API with Chroma. Master metrics like MRR and deploy a functional Flask endpoint for real-world application.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

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Build your subject-matter expertise

This course is part of the Chroma, Weaviate & Production RAG Deployment Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

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.

Module details

This module focuses on building the core of your search application. You will learn the fundamental concepts behind semantic search, explore the Chroma vector database, and get hands-on experience indexing a document collection. By the end of this module, you will have a functional search engine capable of retrieving documents based on semantic meaning.

What's included

3 videos2 readings1 assignment1 ungraded lab

3 videosTotal 15 minutes

From Keywords to Understanding: The Power of Semantic Search5 minutes
Chroma: The Vector Database for Semantic Search5 minutes
Indexing Documents with Chroma5 minutes

2 readingsTotal 20 minutes

The Core Concepts: Embeddings and Vector Databases7 minutes
[Ungraded Lab] Hands On Learning: Build and Query a Chroma Collection13 minutes

1 assignmentTotal 5 minutes

Knowledge Check: Embedding Model Evaluation and Benchmarking5 minutes

1 ungraded labTotal 13 minutes

Hands-On Learning: Build and Query a Chroma Collection13 minutes

A search engine is only as good as its results. In this module, you'll learn how to quantitatively measure search quality. You will explore industry-standard relevance metrics, build a Python script to implement them, and prepare to benchmark your search engine's performance objectively.

What's included

2 videos2 readings1 assignment1 ungraded lab

2 videosTotal 10 minutes

Objective Metrics: From Opinion to Production-Ready5 minutes
Evaluating Semantic Search with MRR and Precision@55 minutes

2 readingsTotal 15 minutes

How to Measure Relevance: MRR & Precision@5 Explained7 minutes
[Ungraded Lab] Hands On Learning: Implement Your Evaluation Script8 minutes

1 assignmentTotal 20 minutes

Hands-On Learning: Calculating Relevance Metrics20 minutes

1 ungraded labTotal 10 minutes

Hands-On Learning: Implement Your Evaluation Script10 minutes

In this final module, you will turn your local search script into a shareable, production-style service. You'll learn to wrap your Chroma engine in a simple web API using Flask, analyze its performance, and consider the trade-offs of different models. This module culminates in the final project where you will build, deploy, and evaluate your complete semantic search API.