Creating AI Applications using Retrieval-Augmented Generation (RAG)
Learn how to give your large language model the powers of retrieval with RAG, and build a RAG app with Streamlit and ChromaDB.
Skill level
IntermediateTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary2 hoursPrerequisites
2 coursesWe suggest you complete the following courses before you get started with Creating AI Applications using Retrieval-Augmented Generation (RAG):- Intro to OpenAI API
- Learn Prompt Engineering
About this course
Unlock the full potential of large language models (LLMs) by integrating external data sources through Retrieval Augmented Generation (RAG). This course will teach you to build AI systems that can search, retrieve, and cite information from documents, enabling more reliable and context-aware responses. You’ll also learn how to create advanced AI-powered search applications with Streamlit and ChromaDB. Ideal for learners with a basic understanding of Python and machine learning concepts.
Skills you'll gain
Compare semantic similarity across large datasets with embeddings models
Engineer effective RAG prompts that allow you to chat with your data
Build a RAG (Retrieval Augmented Generation) app using Streamlit, Chroma and OpenAI
Syllabus
3 lessons • 3 quizzesCertificate of completion available with Plus or Pro
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Reviews from learners
- The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.ChrisCodecademy Learner @ USA
- I felt like I learned months in a week. I love how Codecademy uses learning by practice and gives great challenges to help the learner to understand a new concept and subject.RodrigoCodecademy Learner @ UK
- Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.John-AndrewCodecademy Learner @ USA
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Frequently asked questions about Creating AI Applications using Retrieval-Augmented Generation (RAG)
Retrieval Augmented Generation (RAG) is a technique used to supplement AI applications with an external knowledge source. RAG allows an AI app to ask questions about various forms of uploaded text data and get a verifiable, cited answer.
Join over 50 million learners and start Creating AI Applications using Retrieval-Augmented Generation (RAG) today!
Looking for something else?
Related resources
- Article
Building a Language Model Application with LangChain: A Beginners Guide
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Getting Started with OpenAI Models
Learn how to use an OpenAI model and fine-tune it tailoring it to better fit tasks or topics. - Article
How to Distribute and Publish Your App
Learn how to send your App out for testing, and how to submit it for App Store review.
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Learn the basics of large language models (LLMs) and text-based Generative Artificial Intelligence (AI). We’ll show you how LLMs work and how they’re used.Beginner Friendly< 1 hour
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Guided projects that help you solidify the skills and concepts you're learning.Assessments
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