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)
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
- Basic understanding of technology - superficial exposure to Hadoop is enough.
- 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
Just wanted to send along an important note for anyone learning a cloud technology like GCP - please be sure to delete your projects, instances and in general to free up your resources after you are done using them. Resources like BigTable, Cloud Spanner are pretty expensive - if you happen to create one, then forget to free it up, you could be hit with real sticker shock when you get your next invoice.
Just something important to keep in mind if you are new to using pay-as-you-go technologies:-)
An important note for anyone learning a cloud technology like GCP - please be sure to delete your projects, instances and in general to free up your resources after you are done using them. Resources like BigTable, Cloud Spanner are pretty expensive - if you happen to create one, then forget to free it up, you could be hit with real sticker shock when you get your next invoice.
Just something important to keep in mind if you are new to using pay-as-you-go technologies:-)