Google Cloud Professional Cloud Architect Cert Prep: 5 Managing Implementation

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Noah Gift

1:18:53

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01 Overview.mp4

02:07

02 Makefiles made easy A comprehensive guide.mp4

02:41

03 Configuring your bashrc for an optimal environment.mp4

11:57

04 Implementing continuous integration for Rust with GitHub actions.mp4

07:52

05 Unit testing in Rust A hands-on demonstration.mp4

06:44

06 Supercharging Rust development with Copilot.mp4

09:15

07 Setting up a GCP workstation for Python development.mp4

04:45

08 Mastering Google Cloud Shell A practical guide.mp4

04:23

09 Streamline your development with Google Cloud Editor.mp4

04:41

10 Getting started with the Google Cloud CLI SDK.mp4

06:18

11 Unleashing the power of Google Clouds gcloud command-line tool.mp4

04:50

12 Deploying Rust applications to App Engine A step-by-step guide.mp4

05:15

13 Demo Launching Go applications on Google App Engine.mp4

05:08

14 Wrapping up and next steps in your GCP journey.mp4

02:57

Description

This course prepares you for the Professional Cloud Architect certification exam. A Google Cloud Certified Professional Cloud Architect enables organizations to leverage Google Cloud technologies. Through an understanding of cloud architecture and Google technology, this individual designs, develops, and manages robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.

In this fifth course in the certification prep series, Noah Gift covers topics relating to managing implementation. Noah explains how to best advise development and operation teams to ensure successful deployment of a solution—from configuring your bashrc for an optimal environment to implementing continuous integration for Rust with GitHub actions, and more. He explains the importance of interacting with Google Cloud programmatically, showing you how to master Cloud Shell, streamline your development with Cloud Editor, and unleash the power of Google Cloud's gcloud command-line tool.

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Cloud Computing

Google Cloud

Noah Gift

Instructor's Courses

Author of Practical MLOps, Enterprise MLOps, Developing on AWS with C#, Pragmatic AI, and Python for DevOps. Certified on Multiple MLOps certifications including Google-Professional Machine Learning Engineer and AWS Certified Machine Learning - Specialty. Adjunct Professor at Duke MIDS & Northwestern Graduate Data Science & AI. Held business roles including CTO, general manager, consulting CTO, and cloud architect. Consults with start-ups and other companies on machine learning and cloud architecture. AWS ML Hero, Python Software Foundation Fellow, AWS Subject Matter on Machine Learning, AWS Certified Solutions Architect, AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, Google Certified Professional Architect, and AWS Academy Accredited Instructor. Published books, videos, and courses on cloud machine learning, DevOps, Python, Data Science, Big Data and AI. ★ Specialties ★ ° Cloud-native Machine Learning and AI ° Directly teaching cutting edge skills to students that lead to jobs ° Creating world-class content in all forms ° Building Companies ° Shipping new Products ° Leading and growing engineering teams ° Production Machine Learning, Deep Learning, Big Data, and AI ° Serverless Data Engineering ° Advising Early Stage Startups/Consulting CTO services ° Distributed Systems and Scalability

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