> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo-platform/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo-platform/_mcp/server.

# Tutorials

<a id="safe-synthesizer-tutorials" />

Learn how to run NeMo Safe Synthesizer jobs through hands-on tutorials to generate private synthetic versions of sensitive tabular datasets. Each tutorial provides step-by-step guidance with executable code examples.

## Prerequisites

Before starting any tutorial, ensure you have:

* [NeMo Safe Synthesizer running](/documentation/synthesize-safe-data)
* Python environment with the PyPI `nemo-platform` wrapper package installed. The `all` extra is defined by the wrapper package, not by the generated SDK package under `sdk/python/nemo-platform/pyproject.toml`. If you are working from a source checkout, run `make bootstrap` from the repository root instead.

```bash
pip install "nemo-platform[all]"
```

* Jupyter environment for running tutorial notebooks

***

## Getting Started

Learn the basics with your first Safe Synthesizer job, leveraging smart defaults. This tutorial covers uploading data, running a synthesis job with PII replacement, and reviewing evaluation reports.

**Topics covered:**

* Installing the SDK
* Connecting to Safe Synthesizer
* Using `SafeSynthesizerJobBuilder`
* Monitoring job progress
* Retrieving synthetic data and evaluation reports

<small>
  beginner

   

  20 minutes
</small>

***

## Advanced Topics

Apply differential privacy to achieve the maximum level of privacy with mathematical guarantees. This tutorial explores the privacy-utility tradeoff and how to configure differential privacy parameters.

**Topics covered:**

* Understanding differential privacy concepts (epsilon, delta)
* Configuring privacy hyperparameters
* Privacy budget analysis
* Evaluating privacy-utility tradeoffs
* Interpreting privacy metrics

<small>
  intermediate

   

  1.5 hours
</small>

***

## Additional Resources

After completing these tutorials, explore:

* **[index](/documentation/synthesize-safe-data/about)**: Understand core concepts and components

***

## Need Help?

* Check the [GitHub Issues](https://github.com/NVIDIA/GenerativeAIExamples/issues) for known issues
* Review the [jobs](/documentation/synthesize-safe-data/about/jobs) guide for job management