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Learning Path: Db2 for AI

Level Topic Type
100 A developers guide to data for AI Blog
101 Collect home sales data using a high performance CRUD app Pattern
201a Predict home value using Golang and in-memory database machine learning functions Pattern
201b Predict home value using Python and machine learning Pattern

This learning path demonstrates how data engineers and data scientist can predict the price of a house based on historical data. Using code patterns with sample code, you’ll learn about built-in stored procedures, building machine learning models, and using IBM Db2 Warehouse on Cloud to create a web application using Node.js to create, update, and delete records from the database.

To get started, click on a card below, or see the table above for a complete list of topics covered.

A developers guide to Db2 for AI

Learn about:

  • Stored procedures for machine learning
  • Computer vision
  • Connectors for popular languages
  • VSCode extension, Db2Connect

Collect home sales data using a high performance CRUD app

Learn about:

  • Creating IBM Db2 Warehouse on Cloud
  • Building an app to store data to IBM Db2 Warehouse on Cloud
  • Creating frontend UI with Angular
  • Creating entities

Predict home value using Golang and in-memory database machine learning functions

Learn about:

  • Loading data into IBM Db2 Warehouse on Cloud
  • Enriching data with IBM Db2 Warehouse on Cloud
  • Creating a linear regression model
  • Using golang to expose API to predict home values

Predict home value using Python and machine learning

Learn about:

  • Creating a project in Watson Studio
  • Using Jupyter Notebooks in the new project
  • Creating and deploying machine learning models
  • Using machine learning to forcast home sales prices


Next: A developers guide to data for AI

IBM AI and Data team