Introduction to Neo4j with Python, LangChain & OpenAI

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Ali Binkowska

1:09:30

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1. Introduction

1.1 contactme.001.zip

1.2 Cypher Queries.pdf

1.3 Neo4j Cheat Sheet.pdf

1. Introduction to the Course.mp4

01:17

2. About Neo4j Cheat Sheet.mp4

00:36

3. Into the Cheat Sheet.mp4

00:53

4. Introduction to Graph Database.mp4

01:43

5. Structure of Cypher language.mp4

00:43

6. Introduction to document Cypher Queries document.mp4

00:43

7.1 Link to CSV Files that We Gonna to Use to Create Neo4j Database.html

7. About the Data.mp4

02:20

8. Summary of the Chapter.mp4

00:47

9. Quiz #1.html

2. Neo4j create database with Cypher language

1. Introduction to the Chapter.mp4

00:32

2.1 Aura Graph Database.html

2. Create access to AuraDB.mp4

00:54

3. New DB Instance Accessing CSV Files.mp4

02:18

4. Create Constraints.mp4

00:54

5. Import Data Create Title Nodes.mp4

01:32

6. Import Data Create Skill Nodes.mp4

00:52

7. Visualise Graph.mp4

01:22

8. Import Data skills properity.mp4

01:42

9. Relationship Between Nodes.mp4

01:39

10. Introduce Schema Procedures.mp4

01:24

11. Creating Another Label for Existing Nodes.mp4

02:31

12. Visualize Graph.mp4

02:14

13. Performance of a Query.mp4

02:33

14. Summary of the Chapter.mp4

00:37

15. Quiz #2.html

3. Vector Index

1. Introduction to the Chapter.mp4

00:26

2. Data Import Import Embeddings.mp4

02:15

3. Create Index.mp4

02:21

4. Summary of the Chapter.mp4

00:29

4. Neo4j with Python

1. Introduction to the Chapter.mp4

00:24

2.1 Repository Initial Code for the Project.html

2. Clone Repository with Initial Code.mp4

00:20

3. Credentials & Cypher Queries.mp4

02:59

4. Package Requirements.mp4

00:32

5. CSV Files.mp4

00:25

6. Files main.py & utils.py.mp4

01:30

7. Connect Neo4j Database with Python Driver.mp4

03:30

8. Update utils.py File.mp4

01:01

9. Execute Cypher Queries Using Python Script.mp4

03:22

10. Creating Embeddings - Example Script.mp4

01:35

11. Vector Index with Python Code.mp4

02:57

12. Tidy Up Created Code.mp4

01:50

13. Summary.mp4

00:46

5. LangChain & Plugging Neo4j into an LLM

1. Introduction to the Chapter.mp4

00:20

2. Connecting Neo4j Using LangChain.mp4

01:26

3. Create Prompt & Chain.mp4

02:10

4. Querying the Schema with LLM.mp4

01:18

5. Connecting Vector Index.mp4

02:00

6. Create Chain to Query Vector Index with LLM.mp4

01:59

7. Run Another Question.mp4

01:08

8. Summary of the Chapter.mp4

00:42

9. Technical Summary.mp4

00:42

10. Summary of the Course.mp4

00:57

Description

From CSV to Neo4j Database with Vector Index: Plug Your Data into LLM

What You'll Learn?

Basics of Neo4j
Basics of Cypher language used to query Neo4j
How to create graph database using CSV files
How to create embeddings
How to create vector index based on embeddings
How to work with Neo4j with Python
How to plug Neo4j into ChatGPT using LangChain

Who is this for?

Anyone with basic knowledge of Python who want to turn CSV into Neo4j database and plug it into an LLM

What You Need to Know?

Python Basics

More details

Description
Dive into the world of graph databases with 'Introduction to Neo4j with Python, LangChain & OpenAI'.
This course guides you gently from the very basics of creating Neo4j database via a web browser.
We will use AuraDB, cloud-based service by Neo4j that enables us to create one free instance of the database.
On the way you will learn how to interact with the database using Cypher language.

Next, we will use simple Python code for powerful data work. Initial code will be provided via repository.
We'll also play with LangChain and OpenAI to make your data come alive.
As we are gaining to use new Neo4j capability to create vector index, we will look at the data from two angles:
- we will query database schema, using LLM as a translator of questions into cypher queries
- we will query vector index using embeddings imported into the database
We will briefly also touch on the subject of creating embeddings for the data stored in the database.

No heavy tech talk, just clear steps and support for your learning journey.
As part of the training comes Neo4j Cheat Sheet and a list of cypher queries used in the project with detailed explanation.
With that, knowledge from the course can be transferred to another project that uses Neo4j and Python.

Join me to unlock the potential of your data with Neo4j!
Who this course is for:
Anyone with basic knowledge of Python who want to turn CSV into Neo4j database and plug it into an LLM

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With over eighteen years of experience in multinational corporations, including five impactful years abroad, I’ve developed a deep understanding of recruitment, team leadership, and tailored training programs, strengthened by industry-specific certifications.My journey in Machine Learning and Artificial Intelligence is driven by a vision: to blend my people management and business acumen with cutting-edge tools, enhancing talent development and management processes.

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