• Online, Self-Paced
Course Description

BigQuery is a flagship product on the Google Cloud Platform which allows you to build and train machine learning (ML) models using simple SQL queries. BigQuery has support for a range of supervised and unsupervised machine learning models that can be trained on data stored in BigQuery.

In this course, you will be introduced to BigQuery on the Google Cloud Platform and set up a GCP trial account that allows you to work with BigQuery to train ML models. You will then review some machine learning basics and dig a little deeper into regression models. Next, you will create datasets and tables in BigQuery and upload your data to the cloud. You will visualize and explore your data using Looker Studio and prepare and clean your data using DataPrep. Finally, you will train regression models using linear regression, gradient-boosted trees, and the random forest model and evaluate and compare the performance of these models on your test data.

Learning Objectives

{"discover the key concepts covered in this course"}

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Systems Architecture