# Tutorial Syllabus

<img src="../assets/nouns/tutorial.png" alt="Video Tutorial by artworkbean from the Noun Project" />

Coding samples in the following notebooks help illustrate the use
of **TextGraphs** and related libraries in Python.


## Audience

  * You are a Python programmer who needs to learn how to leverage LLM-augmented workflows to construct KGs
  * You are an ML engineer who needs to understand how to integrate LLM research results into production-quality apps

## Prerequisites

  * Some coding experience in Python (you can read a 20-line program)
  * Some familiarity with ML, specifically with LLM applications
  * Interest in use cases that need to use NLP to construct KGs


## Key Takeaways

  * Hands-on experience with popular open source libraries in Python for natural language at the intersection of LLMs and KGs
  * Coding examples that can be used as starting points for your own related projects
  * Ways to integrate natural language work with other aspects of graph data science