GCP: Complete Google Data Engineer and Cloud Architect Guide

  • Job DurationUdemy
  • Job Duration28 hours worth of material
  • Job DurationPaid Course

Project detail


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)

Languages required