GCP: Complete Google Data Engineer and Cloud Architect Guide

• Basic understanding of technology – superficial exposure to Hadoop is enough

Description

This course is a really comprehensive guide to the Google Cloud Platform – it has ~25 hours of content and ~60 demos.

The Google Cloud Platform is not currently the most popular cloud offering out there – that’s AWS of course – but it is possibly the best cloud offering for high-end machine learning applications. That’s because TensorFlow, the super-popular deep learning technology is also from Google.

What’s Included:

• Compute and Storage – AppEngine, Container Enginer (aka Kubernetes) and Compute Engine
• Big Data and Managed Hadoop – Dataproc, Dataflow, BigTable, BigQuery, Pub/Sub
• TensorFlow on the Cloud – what neural networks and deep learning really are, how neurons work and how neural networks are trained.
• DevOps stuff – StackDriver logging, monitoring, cloud deployment manager
• Security – Identity and Access Management, Identity-Aware proxying, OAuth, API Keys, service accounts
• Networking – Virtual Private Clouds, shared VPCs, Load balancing at the network, transport and HTTP layer; VPN, Cloud Interconnect and CDN Interconnect
• Hadoop Foundations: A quick look at the open-source cousins (Hadoop, Spark, Pig, Hive and HBase)