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)
GCP is one of the fastest-growing cloud platforms in the industry. This course aims to provide a thorough overview of GCP. From the core building blocks such as Compute, Storage, and Networking to the advanced services, this course introduces the key concepts and then shows you how to start being productive. Each section includes a hands-on demo of one of the key services. You will also learn the use cases and scenarios for some of the most significant services of Google Cloud.
What you’ll learn
- Take the first step in your GCP readiness journey
- Explore GCP building blocks
- Understand the key GCP services
- Learn how to use GCP compute, storage, and networking services
- Identify the value proposition of key GCP services
- Choose the right GCP service for your use case and business scenario
- Apply the concepts of identity & access management to secure GCP projects
