Google Cloud for Machine Learning 2020 Master Course
Master Google Cloud with comprehensive coverage of tools like: Serverless, BigQuery, Compute Engine and Cloud Functions
Created by Vinay Phadnis | 10 hours on-demand video course
Cloud Computing is one of the highest paying and most demanding job category in technology. Most businesses in recent years have started using cloud services like database, networking, servers, analytics, and intelligence for their business needs. Using cloud services not only helps with smart usage of infrastructure but also minimizes operational costs.
Google Cloud is quickly gaining market adoption due to some of its offerings in the Data Analytics and Serverless domain. Looking at the future, Google Cloud would be an excellent choice.
This course aims at covering a lot of the most used Google cloud products.
- App Engine: App Engine is one of Google Cloud’s serverless platforms. App Engine enables you to create infinitely scalable applications and deployments. In this section, you will be able to, Create an app engine project on Google Cloud. Host a static website on App Engine. Create an API using App Engine.
- Cloud Compute Engine: Cloud compute engine is Google Cloud’s offering for the Virtual Machine space. You can create a Virtual machine with complete custom hardware and software. In this section, we will be creating a Virtual Machine on Google Cloud and create a CPU intensive program to benchmark the Virtual Machine.
- Cloud Firestore: Cloud Firestore is a fully managed NoSQL database platform offered by Google Cloud and Firebase. We will be performing CRUD operations with Firebase and use it with App Engine.
- Cloud BigQuery: Cloud BigQuery is Google Cloud’s offering for big data related workloads. In this section, we will be creating a custom dataset using Python, we will host this dataset on Cloud BigQuery and then perform SQL queries on the database
Overall, this course aims at providing a holistic understanding of the software development cycle on Google Cloud. Most of the essential steps from writing code to staging deployments using Git and GitHub are covered in this course.
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