# Add credentials to the Signals prospect scoring ML notebook
> Configure Google Colab notebook with Snowplow Signals credentials for the prospect scoring machine learning tutorial.
> Source: https://docs.snowplow.io/tutorials/signals-ml-prospect-scoring/setup/
> Documentation index: https://docs.snowplow.io/llms.txt

[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/snowplow-incubator/signals-notebooks/blob/main/web/web_prospect_scoring_end_to_end.ipynb)

For ML training data we will use an artificial set of Snowplow events. Feel free to replace with your warehouse connection to connect to your own dataset.

Start by configuring your Signals credentials in the notebook.

![Google Colab Secrets panel showing the notebook secrets configured for your Signals credentials, with their values hidden](/assets/images/colab_credentials-75693a10119a3fbb3b31d8567f3c1a7c.jpeg)

Here's a list of all the credentials you may need to configure, saved as variables:

```python
from google.colab import userdata

# Snowplow Signals Console credentials
SP_API_URL = userdata.get('SP_API_URL')       # Signals API URL
SP_API_KEY = userdata.get('SP_API_KEY')       # Signals API key
SP_API_KEY_ID = userdata.get('SP_API_KEY_ID') # Signals API key ID
SP_ORG_ID = userdata.get('SP_ORG_ID')         # Snowplow org ID
```

Once you've added the secrets, start working through the tutorial. If you prefer to run the cells in one go with Run all, update your details in the required places first - they're marked with `UPDATE THIS`.