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In this module you will learn how to write Cypher code to retrieve data from the graph. You will learn how to:- Retrieve nodes from the graph.- Retrieve nodes with a particular label.- Filter the retrieval by a property value.- Return property values.- Retrieve nodes and relationships from the graph using patterns in the graph.- Filter queriesUsing the Movies example dataset, you will create and execute Cypher code to find actors and movies in our graph.

Presenter: Martin O'Hanlon

Full Course: https://graphacademy.neo4j.com/courses/cypher-fundamentals/

In this module you will learn how to write Cypher code to retrieve data from the graph. You will learn how to:- Retrieve nodes from the graph.- Retrieve nodes with a particular label.- Filter the retrieval by a property value.- Return property values.- Retrieve nodes and relationships from the graph using patterns in the graph.- Filter queriesUsing the Movies example dataset, you will create and execute Cypher code to find actors and movies in our graph.

Presenter: Martin O'Hanlon

Full Course: https://graphacademy.neo4j.com/courses/cypher-fundamentals/

In this module you will learn how to write Cypher code to retrieve data from the graph. You will learn how to:- Retrieve nodes from the graph.- Retrieve nodes with a particular label.- Filter the retrieval by a property value.- Return property values.- Retrieve nodes and relationships from the graph using patterns in the graph.- Filter queriesUsing the Movies example dataset, you will create and execute Cypher code to find actors and movies in our graph.

Presenter: Martin O'Hanlon

Full Course: https://graphacademy.neo4j.com/courses/cypher-fundamentals/

In this module you will learn how to write Cypher code to retrieve data from the graph. You will learn how to:- Retrieve nodes from the graph.- Retrieve nodes with a particular label.- Filter the retrieval by a property value.- Return property values.- Retrieve nodes and relationships from the graph using patterns in the graph.- Filter queriesUsing the Movies example dataset, you will create and execute Cypher code to find actors and movies in our graph.

Presenter: Martin O'Hanlon

Full Course: https://graphacademy.neo4j.com/courses/cypher-fundamentals/

Discover the power of integrating Neo4j with Generative AI models through Langchain.

Learn how to harness graph databases to enhance the accuracy and reliability of Large Language Models (LLMs) by grounding them with factual information, effectively preventing misinformation or 'hallucinations.' We go hands-on using Langchain and Python to seamlessly connect an LLM with Neo4j, leveraging Cypher and Vector Indexes for robust AI applications. Although our focus is on OpenAI models, Langchain's versatility allows for the exploration of various LLMs.

Presenter: Martin O'Hanlon

Full Course: https://graphacademy.neo4j.com/courses/llm-fundamentals/

Discover the power of integrating Neo4j with Generative AI models through Langchain.

Learn how to harness graph databases to enhance the accuracy and reliability of Large Language Models (LLMs) by grounding them with factual information, effectively preventing misinformation or 'hallucinations.' We go hands-on using Langchain and Python to seamlessly connect an LLM with Neo4j, leveraging Cypher and Vector Indexes for robust AI applications. Although our focus is on OpenAI models, Langchain's versatility allows for the exploration of various LLMs.

Presenter: Martin O'Hanlon

Full Course: https://graphacademy.neo4j.com/courses/llm-fundamentals/

Discover the power of integrating Neo4j with Generative AI models through Langchain.

Learn how to harness graph databases to enhance the accuracy and reliability of Large Language Models (LLMs) by grounding them with factual information, effectively preventing misinformation or 'hallucinations.' We go hands-on using Langchain and Python to seamlessly connect an LLM with Neo4j, leveraging Cypher and Vector Indexes for robust AI applications. Although our focus is on OpenAI models, Langchain's versatility allows for the exploration of various LLMs.

Presenter: Martin O'Hanlon

Full Course: https://graphacademy.neo4j.com/courses/llm-fundamentals/

Discover the power of integrating Neo4j with Generative AI models through Langchain.

Learn how to harness graph databases to enhance the accuracy and reliability of Large Language Models (LLMs) by grounding them with factual information, effectively preventing misinformation or 'hallucinations.' We go hands-on using Langchain and Python to seamlessly connect an LLM with Neo4j, leveraging Cypher and Vector Indexes for robust AI applications. Although our focus is on OpenAI models, Langchain's versatility allows for the exploration of various LLMs.

Presenter: Martin O'Hanlon

Full Course: https://graphacademy.neo4j.com/courses/llm-fundamentals/