GCP: Complete Google Data Engineer and Cloud Architect Guide

About this course

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 EngineBig 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 managerSecurity - Identity and Access Management, Identity-Aware proxying, OAuth, API Keys, service accountsNetworking - Virtual Private Clouds, shared VPCs, Load balancing at the network, transport and HTTP layer; VPN, Cloud Interconnect and CDN InterconnectHadoop Foundations: A quick look at the open-source cousins (Hadoop, Spark, Pig, Hive and HBase)

Course objectives

• to equip students with knowledge of cloud computing fundamentals
• to develop skills in using Google Cloud tools for data engineering
• to provide insights into deploying and managing machine learning applications