It’s not hyperbole to say that cloud computing is among the hottest sectors in all of tech. It is used in pretty much any app, game, or service that you use. The world increasingly relies on the cloud.
Knowing how to build, grow, and maintain a cloud-based network for Google Cloud. Moreover, an understanding of components and tools such as Machine Learning, TensorFlow, and Kubernetes is incredibly valuable.
The Google Cloud Platform might not be the most popular cloud offering around, but it may be the best cloud offering. Why? Because TensorFlow, the extremely popular deep learning technology also comes from Google.
This comprehensive guide to TensorFlow and the Google Cloud Platform will help put you on certification track to become a Google Data Engineer or Cloud Architect.
Features
- Access 166 lectures & 22 hours of content 24/7
- Cover the material you need to pass Google Data Engineer & Cloud Architect certification exams
- Explore AppEngine, Kubernetes, & Compute Engine
- Discuss Big Data & Managed Hadoop w/ Dataproc, Dataflow, BigTable, BigQuery, & more
- Learn what neural networks & deep learning are, how neurons work, & how neural networks are trained
- Understand DevOps principles like StackDrive logging, monitoring, & cloud deployment management
- Discover security, networking, & Hadoop foundations
Availabity
Normally this much education would cost you about $200, and that’s actually worth it. With more than 22 hours of education, there’s some 166 lectures to bring you up to speed. But, for a limited time, we’ll do you one better. Pick up a lifetime license to the GCP: Complete Google Data Engineer and Cloud Architect Guide for just $15, a savings of some 92%.
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