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Learner Reviews & Feedback for Knowledge Graphs for RAG by DeepLearning.AI

4.7
stars
31 ratings

About the Course

Knowledge graphs are used in development to structure complex data relationships, drive intelligent search functionality, and build powerful AI applications that can reason over different data types. Knowledge graphs can connect data from both structured and unstructured sources (databases, documents, etc.), providing an intuitive and flexible way to model complex, real-world scenarios. Unlike tables or simple lists, knowledge graphs can capture the meaning and context behind the data, allowing you to uncover insights and connections that would be difficult to find with conventional databases. This rich, structured context is ideal for improving the output of large language models (LLMs), because you can build more relevant context for the model than with semantic search alone. This course will teach you how to leverage knowledge graphs within retrieval augmented generation (RAG) applications. You’ll learn to: 1. Understand the basics of how knowledge graphs store data by using nodes to represent entities and edges to represent relationships between nodes. 2. Use Neo4j’s query language, Cypher, to retrieve information from a fun graph of movie and actor data. 3. Add a vector index to a knowledge graph to represent unstructured text data and find relevant texts using vector similarity search. 4. Build a knowledge graph of text documents from scratch, using publicly available financial and investment documents as the demo use case 5. Explore advanced techniques for connecting multiple knowledge graphs and using complex queries for comprehensive data retrieval. 6. Write advanced Cypher queries to retrieve relevant information from the graph and format it for inclusion in your prompt to an LLM. After course completion, you’ll be well-equipped to use knowledge graphs to uncover deeper insights in your data, and enhance the performance of LLMs with structured, relevant context....

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1 - 8 of 8 Reviews for Knowledge Graphs for RAG

By Agrover112

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Jul 2, 2024

Interesting overview into creating a KG using Neo4J and integrating it with LangChain for RAG!

By Ilija D

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Oct 30, 2024

Compact but great course. It doesn't go into deep into Neo4j or RAG, but it introduces new ways in which you could solve problems and improve your pipeline. However, it is not suitable for beginners.

By Vineet K

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Aug 18, 2024

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By Tung L D

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Nov 12, 2024

very helpful

By Reza G

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Jan 14, 2025

The notebooks are very well organized and deserve a 5-star, but the video lectures are difficult to follow. It seems like a 3–4-hour course is jammed into an hour. There are times the instructor spends 5 seconds on a large important chunk of code which makes it difficult even to pause on the right frame.

By francisco v i

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Nov 18, 2024

Muy buen curso, muy detallado el script. Me parece hacen referencia a un video que no se reproduce en coursera (debe ser de la plataforma OpenAI)

By Adiarray J

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Sep 23, 2024

simply

By Zahra S

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Nov 3, 2024

It would be also beneficial to have some (optional) video or reading to go over the syntax and structure of cypher and neo4j. I could understand mostly, but I cannot write new queries.