GCP: Complete Google Data Engineer and Cloud Architect Guide

The Google Cloud for ML with TensorFlow, Big Data with Managed Hadoop

What you'll learn:

• Deploy Managed Hadoop apps on the Google Cloud
• Build deep learning models on the cloud using TensorFlow
• Make informed decisions about Containers, VMs and AppEngine
• Use big data technologies such as BigTable, Dataflow, Apache Beam and Pub/Sub

This course is a really comprehensive guide to the Google Cloud Platform - it has ~25hours 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, APIKeys, service accounts
• Networking - Virtual Private Clouds, shared VPCs, Load balancing at the network, transport and HTTP layer; VPN, Cloud Interconnect and CDNInterconnect
• Hadoop Foundations: A quick look at the open-source cousins (Hadoop, Spark, Pig, Hiveand HBase)