Complete Google Data Engineer and Cloud Architect Guide | Simpliv

<div class="about-course">

<div class="course-info course-margin">

<div class="description">

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:

<ul>

<li>Compute and Storage - AppEngine, Container Enginer (aka Kubernetes) and Compute Engine</li>

<li>Big Data and Managed Hadoop - Dataproc, Dataflow, BigTable, BigQuery, Pub/Sub</li>

<li>TensorFlow on the Cloud - what neural networks and deep learning really are, how neurons work and how neural networks are trained.</li>

<li>DevOps stuff - StackDriver logging, monitoring, cloud deployment manager</li>

<li>Security - Identity and Access Management, Identity-Aware proxying, OAuth, API Keys, service accounts</li>

<li>Networking - Virtual Private Clouds, shared VPCs, Load balancing at the network, transport and HTTP layer; VPN, Cloud Interconnect and CDN Interconnect</li>

<li>Hadoop Foundations: A quick look at the open-source cousins (Hadoop, Spark, Pig, Hive and HBase)</li>

</ul>

Who is the target audience?

<ul>

<li>Yep! Anyone looking to use the Google Cloud Platform in their organizations</li>

<li>Yep! Any one who is interesting in architecting compute, networking, loading balancing and other solutions using the GCP</li>

<li>Yep! Any one who wants to deploy serverless analytics and big data solutions on the Google Cloud</li>

<li>Yep! Anyone looking to build TensorFlow models and deploy them on the cloud</li>

</ul>

</div>

</div>

</div>

<div class="about-course">

<div class="course-info">

<div class="about-title">

<div class="course-headers">Basic knowledge</div>

</div>

<div class="description">

<ul>

<li>Basic understanding of technology - superficial exposure to Hadoop is enough.</li>

</ul>

</div>

</div>

</div>

<div class="about-course">

<div class="course-info">

<div class="about-title">

<div class="course-headers">What you will learn</div>

</div>

<div class="description">

<ul>

<li>Deploy Managed Hadoop apps on the Google Cloud</li>

<li>Build deep learning models on the cloud using TensorFlow</li>

<li>Make informed decisions about Containers, VMs and AppEngine</li>

<li>Use big data technologies such as BigTable, Dataflow, Apache Beam and Pub/Sub</li>

</ul>

</div>

</div>

</div>