GCP: Complete Google Data Engineer and Cloud Architect Guide

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)

BASIC KNOWLEDGE

• Basic understanding of technology - superficial exposure to Hadoop is enough.

Who is the target audience?

• Yep! Anyone looking to use the Google Cloud Platform in their organizations
• Yep! Any one who is interesting in architecting compute networking loading balancing and other solutions using the GCP
• Yep! Any one who wants to deploy serverless analytics and big data solutions on the Google Cloud
• Yep! Anyone looking to build TensorFlow models and deploy them on the cloud

Course Completion Certificate

What you will 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

Curriculum:

You This Course and Us

Introduction

• Compute
• Storage
• Cloud SQL Cloud Spanner - OLTP - RDBMS
• Hadoop Pre - reqs and Context
• BigTable - HBase - Columnar Store
• Datastore - Document Database
• BigQuery - Hive - OLAP
• Dataflow - Apache Beam
• Dataproc - Managed Hadoop
• Pub/Sub for Streaming
• Datalab - Jupyter
• TensorFlow and Machine Learning
• Regression in TensorFlow
• Vision Translate NLP and Speech: Trained ML APIs
• Virtual Machines and Images
• VPCs and Interconnecting Networks
• Managed Instance Groups and Load Balancing
• Ops and Security
• Appendix: Hadoop Ecosystem

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