Training schedule
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Before working with Google Cloud Platform (GCP), it is important to have the right skills and knowledge. This 1-day Foundation level training is all you need to get started with Big Data and Machine Learning on GCP.
The training offers a combination of presentations, demos, and hands-on labs that introduce you to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). You will learn to process Big Data at scale for analytics and Machine Learning. You will explore the fundamentals of building new machine learning models and creating streaming data pipelines and dashboards.
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What you'll learn
Perfect for Developers, sysadmins, and Solution Architects
- The value of Google Cloud Platform for Big Data & Machine Learning
- How to process Big Data at scale for analytics
- How to leverage GCP service for Machine Learning
- How to create streaming data pipelines and dashboards
The schedule
Introducing Google Cloud Platform
- Google Platform Fundamentals Overview
- Google Cloud Platform Big Data Products
Compute and Storage Fundamentals
- CPUs on demand (Compute Engine)
- A global filesystem (Cloud Storage)
- CloudShell
- Lab: Set up a Ingest-Transform-Publish data processing pipeline
Data Analytics on the Cloud
- 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
Scaling Data Analysis
- Fast random access
- Datalab
- BigQuery
- Lab: Build machine learning dataset
Machine Learning
- Machine Learning with TensorFlow
- Lab: Carry out ML with TensorFlow
- Pre-built models for common needs
- Lab: Employ ML APIs
Data Processing Architectures
- Message-oriented architectures with Pub/Sub
- Creating pipelines with Dataflow
- Reference architecture for real-time and batch data processing
Summary
- Why GCP?
- Where to go from here
- Additional Resources