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)
What you'll learn
understand key Google Cloud services
gain practical skills in big data management
implement machine learning models using TensorFlow on Google Cloud
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