The goal of this session is to give you a hands-on taste on how to use the different features of the DataScience Platform, including conducting analyses, publishing reports, scheduling scripts, and deploying models.

There will be three parts to this demo:

1. Analysis and publishing
2. Scheduling
3. Deploying the model as an API

Analysis and publishing

In this part of the session we'll perform an analysis and then publish these findings as an easily-consumable Report for collaborators and business users.

Procedure:

1. Import and install modules for our analysis.
2. Load our data.
3. Run some analyses.
4. Publish the resulting analysis as an attractive Report.

Scheduling

Next, we’ll show you how to schedule a job so that you can easily automate processes that need to happen on a regular basis (like ingestion of new training data, batch data transformations, and updated predictions).

Deploying the model as an API

Last (but definitely not least), we'll deploy a model as an API using the platform. By deploying the model as an API anyone in the organization with an API key can query it, including any apps that the engineering team has developed.