This Google Cloud Platform Big Data and Machine Learning Fundamentals course introduces students to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
Content
Introducing Google Cloud Platform
- Google Platform Fundamentals Overview.
- Google Cloud Platform Big Data Products.
- CPUs on demand (Compute Engine).
- A global filesystem (Cloud Storage).
- CloudShell.
- Lab: Set up a Ingest-Transform-Publish data processing pipeline.
- Stepping-stones to the cloud.
- Cloud SQL: your SQL database on the cloud.
- Lab: Importing data into CloudSQL and running queries.
- Spark on Dataproc.
- Lab: Machine Learning Recommendations with Spark on Dataproc.
- Fast random access.
- Datalab.
- BigQuery.
- Lab: Build machine learning dataset.
- Machine Learning with TensorFlow.
- Lab: Carry out ML with TensorFlow
- Pre-built models for common needs.
- Lab: Employ ML APIs.
- Message-oriented architectures with Pub/Sub.
- Creating pipelines with Dataflow.
- Reference architecture for real-time and batch data processing.
- Why GCP?
- Where to go from here
- Additional Resources