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Get started > Walkthroughs > Code in 5

Code in 5

Follow five simple steps to get started with DataRobot's code-first experience. This page will outline how to get value out of DataRobot Notebooks as means for engaging with code-centric data science.

1: Learn how to work with DataRobot APIs

DataRobot's API quickstart guide provides the fundamental requirements for you to work with the API. Review its topics to understand any considerations required to engage in a code-first workflow with DataRobot, such as API prerequisites, creating an API Key, and Authenticating with DataRobot.

2: Review the DataRobot Notebook workflow

Use the flowchart below to understand the common workflows for working with DataRobot Notebooks.

graph TB
  A[Create a DataRobot notebook]
  A --> |New notebook|C[Add a new notebook]
  A --> |Existing notebook|D[Upload an .ipynb notebook];
  C --> E{Configure the environment}
  D --> E
  E --> F[Start the notebook session]
  F --> G[Edit the notebook]
  G --> |Writing guidelines?|H[Create and edit Markdown cells]
  G --> |Coding?|I[Reference code snippets and create code cells]
  H --> J[Run the notebook]
  I --> J
  J --> K[Create a revision history]

3: Create a DataRobot Notebook

To add notebooks to DataRobot, navigate to the Notebooks page. This brings you the notebook dashboard, which hosts all notebooks currently available. Simple select Add new > Add notebook to begin working in a DataRobot notebook.

4: Review and import an AI accelerator

If you do not wish to begin coding from scratch, or want to further understand how to leverage DataRobot's capabilities from a code-centric perspective, browse DataRobot's many AI accelerators that outline common use cases and machine learning workflows using version 3.x of DataRobot's Python client.

If a particular use case is satisfactory to you, you can download it from DataRobot's AI accelerator repo and upload it to DataRobot Notebooks to test it, copy code to use as a template, and more to leverage your code-first experience.

Read more about the AI accelerators available for use.

5: Reference sample code snippets in notebooks

As you develop your notebook in DataRobot, you may be trying to find ways to execute specific DataRobot functions. DataRobot provides a set of pre-defined code snippets, inserted as cells in a notebook, for commonly used methods in the DataRobot API as well as other data science tasks. These include connecting to external data sources, deploying a model, creating a model factory, and more. Access code snippets by selecting the code icon in the sidebar.

Updated March 20, 2024