> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo-helix/v0.7.1/documentation/design-synthetic-data/tutorials/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo-helix/_mcp/server.

# Tutorials

These tutorials demonstrate how to build Data Designer configurations and execute them through the NeMo Data Designer plugin.

> **Note**
>
> The code snippets on this page are for conceptual demonstration purposes only.
> For runnable examples, jump ahead to the [Basics](/documentation/design-synthetic-data/tutorials/the-basics) or [Seeding](/documentation/design-synthetic-data/tutorials/seeding-with-external-datasets) tutorial.

## Configuration and Execution

Data Designer separates **configuration** (building dataset schemas) from **execution** (generating the data).

**Part 1: Build Configs (Library)**

Use `data_designer.config` to define your dataset. See the [library documentation](https://docs.nvidia.com/nemo/datadesigner/v0.9.3/getting-started/welcome) for comprehensive guides on column types, constraints, and processors.

```python
import data_designer.config as dd

config_builder = dd.DataDesignerConfigBuilder(model_configs)
config_builder.add_column(dd.SamplerColumnConfig(...))
config_builder.add_column(dd.LLMTextColumnConfig(...))
```

**Part 2: Execute (Plugin)**

Run the configuration with the CLI or SDK:

```bash
nemo data-designer preview product_reviews.py --num-records 5
nemo data-designer create product_reviews.py --num-records 30
```

```python
import os
from nemo_helix_plugin.client.client import NemoClient
from nemo_data_designer_plugin.sdk.resources import DataDesignerResource

client = NemoClient(
    base_url=os.environ.get("NHX_BASE_URL", "http://localhost:8080"),
    workspace="default",
)
data_designer = DataDesignerResource(client)
preview = data_designer.preview(config_builder)
job = data_designer.create(config_builder, num_records=1000)
```

## Prerequisites

Complete [Setup](/documentation/get-started) to ensure you have the NeMo Services running locally and an inference provider available.
These tutorials reference the default NVIDIA Build model provider, which is created as `default/nvidia-build` during setup.

## Tutorials

#### [The Basics](/documentation/design-synthetic-data/tutorials/the-basics)

Generate a product review dataset using samplers and LLM-generated text. Learn the fundamentals of building configurations and executing jobs.

beginner data-designer

#### [Seeding](/documentation/design-synthetic-data/tutorials/seeding-with-external-datasets)

Use external datasets to ground synthetic data generation. Generate realistic patient medical notes from symptom-to-diagnosis data.

intermediate data-designer

#### [Generate Retrieval Training Data](/documentation/design-synthetic-data/tutorials/retrieval-generate)

Turn your own document corpus into judged question-and-answer pairs, ready for embedding fine-tuning. Hard-negative mining uses the current encoder to select non-answer passages that rank near each positive, giving the model useful examples to distinguish.

intermediate data-designer retrieval

## Docs

- [The Basics](https://docs.nvidia.com/nemo-helix/v0.7.1/documentation/design-synthetic-data/tutorials/the-basics.md): 
- [Seeding with External Datasets](https://docs.nvidia.com/nemo-helix/v0.7.1/documentation/design-synthetic-data/tutorials/seeding-with-external-datasets.md): 
- [Generate Retrieval Training Data](https://docs.nvidia.com/nemo-helix/v0.7.1/documentation/design-synthetic-data/tutorials/retrieval-generate.md):