# Model Creator Profile: Model Creator # Learn More at the Squirro Academy [](https://learn.squirro.com) Visit the [Squirro Academy](https://learn.squirro.com/) to learn more about the dedicated [AI Studio Model Creator Certification Course](SquirroNoCodeAIModelCreatorTraining&Certification). Model creators are responsible for creating the machine-learning (ML) models that power Squirro’s AI applications. While ML models can be created outside of Squirro and imported into the platform, Squirro’s AI Studio provides a no-code interface for creating and training models. While it helps to have prior experience with machine learning, model creators do not need a technical background in machine learning to use the AI Studio. This page provides an overview of the Model Creator role and links to relevant parts of Squirro’s documentation. > **Tip** > > The Model Creator role focuses explicitly on creating models within Squirro. For general-purpose data scientist and analyst activities, see the [Data Scientist](data-scientist.md#data-scientist) role. ## Introduction As a model creator, you are responsible for creating and training the machine-learning (ML) models that power Squirro’s AI applications. The primary tool you’ll work with is the Squirro AI Studio, a no-code interface for creating and training ML models. Reference: Learn more by browsing the [AI Studio](../technical/ai-studio/index.md#ai-studio) documentation. ## Importing Existing Models If you have created a model outside of Squirro that you would like to import, see the [Data Scientist](data-scientist.md#data-scientist) profile for an overview of the import process. ## AI Studio The Squirro AI Studio is a no-code interface for creating and training ML models that follows a three-step process outlined below: [](https://s3.amazonaws.com/download.squirro.net/docs/technical/ai-studio/ai-3.png) The three steps to creating a model using AI Studio, with relevent documentation linked, are: 1. [Ground Truth](../technical/ai-studio/ground-truth.md#ai-ground-truths): View your data, identify relevant classes, and label training data. 2. [Train and Publish Models](../technical/ai-studio/models.md#ai-studio-models): Combine a Ground Truth with a ready-to-use ML template to create efficient models. 3. [Deploy Published Models](../technical/ai-studio/publish.md#ai-studio-publish): Select published models and directly deploy them to the ingestion pipeline.