This course is a comprehensive guide to the Google Cloud Platform – it has +20 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.
- Certification Req’s – Covers pretty much all of the material you ought to need to get past the Google Data Engineer and Cloud Architect certification tests
- 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 Essemtials – 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)
What am I going to get from this course?
- 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
Who is the target audience?
- Anyone looking to use the Google Cloud Platform in their organizations
- Anyone looking to clear the Google Data Engineer or Cloud Architect certification tests
- Anyone looking to build TensorFlow models and deploy them on the cloud
We hope to help guide you on your path to becoming a certified Google Data Engineer!