GraphAcademy
Course · Part of Build a Neo4j-backed Application

Introduction to Vector Indexes and Unstructured Data

20 lessons across 3 modules
Generative AI & GraphRAGGenAIProcessingIntermediateContext EngineerBuild a Neo4j-backed Application
About this course

In this course, you will learn

  • Importing unstructured data into graphs

  • Vector indexes

  • Embedding data

  • Chunking

  • Using Neo4j with LangChain

Course content

3 modules, 20 lessons.

  1. 6 lessons
    1. Getting Started
    2. Semantic search
    3. Finding Movie Plots
    4. Vectors
    5. Unstructured data
    6. Searching imagesOptional
  2. 5 lessons
    1. Vectors and Embeddings
    2. Load embeddings
    3. Create a Vector Index
    4. Create the Answer Vector Index
    5. Query a Vector Index
  3. 9 lessons
    1. Setup your development environment
    2. Structured and Unstructured Data
    3. Chunking
    4. Import data with Python and LangChain
    5. Creating embeddings
    6. Create a graph
    7. Extract Topics
    8. Expand the GraphOptional
    9. Turning data into knowledge
Where to next

Keep going on Build a Neo4j-backed Application.

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Constructing Knowledge Graphs with Neo4j GraphRAG for Python

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Evaluating GraphRAG with RAGAS

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Build a ReAct agent with Neo4j and LangChain

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