> ## Documentation Index
> Fetch the complete documentation index at: https://kumo.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Tutorial

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## Introduction

The Kumo predictive query is a declarative syntax for describing a machine learning task. Predictive Queries are written using the Predictive Query Language (PQL), a concise SQL-like syntax that allows you to define a model for a new business problem. Once a Predictive Query is saved, the Kumo platform compiles it into a training plan, which is used to train your model.

In this tutorial, you'll learn the basics for writing an effective predictive query to power your enterprise predictions.

* [Predictive Query Structure](/pquery-structure)
* [Task Types](/task-types)
* [Static vs Temporal Predictive Queries](/temporal-vs-static-pqueries)
* [Commands and Operators](/commands-and-operators)
* [Putting It All Together](/putting-it-all-together)
* [What's Next?](/whats-next)

You can also take a look at various examples [here](/predictive-task-reference).

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What’s Next

* [Examples](/predictive-task-reference)

* [Table of Contents](#)

* * [Introduction](#introduction)