Smart Analytics, Machine Learning, and AI on Google Cloud

Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

• Introduction
• In this module, we introduce the course and agenda
• Introduction to Analytics and AI
• This modules talks about ML options on Google Cloud
• Prebuilt ML model APIs for Unstructured Data
• This module focuses on using pre-built ML APIs on your unstructured data
• Big Data Analytics with Notebooks
• This module covers how to use Notebooks
• Production ML Pipelines
• This module covers building custom ML models and introduces Vertex AI and TensorFlow Hub
• Custom Model building with SQL in BigQuery ML
• This module covers BigQuery ML
• Custom Model Building with Vertex AI AutoML
• Custom model building with Vertex AI AutoML
• Summary
• This module recaps the topics covered in the course