Module 1: Introduction to Google Cloud

• Identify the different aspects of Google Cloud’s infrastructure
• Identify the big data and ML products that form Google Cloud

Module 2: Product Recommendations Using Cloud SQL and Spark

• Review how businesses use recommendation models
• Evaluate how and where you will compute and store your housing rental model results
• Analyse how running Hadoop in the cloud with Dataproc can enable scale
• Evaluate different approaches for storing recommendation data off-cluster

Module 3: Predicting Visitor Purchases Using BigQuery ML

• Analyse big data at scale with BigQuery
• Learn how BigQuery processes queries and stores data at scale
• Walkthrough key ML terms: features, labels, training data
• Evaluate the different types of models for structured datasets
• Create custom ML models with BigQuery ML

Module 4: Real-time Dashboards with Pub / Sub, Dataflow, and Google Data Studio

• Identify modern data pipeline challenges and how to solve them at scale with Dataflow
• Design streaming pipelines with Apache Beam
• Build collaborative real-time dashboards with Data Studio

Module 5: Deriving Insights from Unstructured Data Using Machine Learning

• Evaluate how businesses use unstructured ML models and how the models work
• Choose the right approach for machine learning models between pre-built and custom
• Create a high-performing custom image classification model with no code using AutoML