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Google Cloud Digital Leader Certification Guide

Google Cloud Digital Leader Certification Guide

By : Bruno Beraldo Rodrigues
5 (4)
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Google Cloud Digital Leader Certification Guide

Google Cloud Digital Leader Certification Guide

5 (4)
By: Bruno Beraldo Rodrigues

Overview of this book

To thrive in today's world, leaders and technologists must understand how technology shapes businesses. As organizations shift from self-hosted to cloud-native solutions, embracing serverless systems, strategizing data use, and defining monetization becomes imperative. The Google Cloud Digital Leader Certification Guide lays a solid foundation of industry knowledge, focused on the Google Cloud platform and the innovative ways in which customers leverage its technologies. The book starts by helping you grasp the essence of digital transformation within the Google Cloud context. You’ll then cover core components of the platform, such as infrastructure and application modernization, data innovation, and best practices for environment management and security. With a series of practice exam questions included, this book ensures that you build comprehensive knowledge and prepare to certify as a Google Cloud Digital Leader. Going beyond the exam essentials, you’ll also explore how companies are modernizing infrastructure, data ecosystems, and teams in order to capitalize on new market opportunities through platform expertise, best practices, and real-world scenarios. By the end of this book, you'll have learned everything you need to pass the Google Cloud Digital Leader certification exam and have a reference guide for future requirements.
Table of Contents (21 chapters)
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1
Part 1:Introduction to Digital Transformation with Google Cloud
5
Part 2:Innovating with Data and Google Cloud
9
Part 3:Infrastructure and Platform Modernization
13
Part 4:Understanding Google Cloud Security and Operations
17
Part 5:Practice Exam Questions

AI overview and Google’s contribution

Google has made meaningful contributions in several areas of the ML and AI space. At a high level, Google has been doing research and development in the ML space for a long time, where they’ve developed frameworks such as TensorFlow, which makes it easier to train ML models. Google also has an extensive library of models that they developed themselves, which can be applied across a variety of data and use cases. One of the most impactful projects in the natural language processing space was the development of the Transformer architecture, the foundation upon which the generative AI revolution was built. What’s interesting about the Transformer architecture is that it is based on the self-attention mechanism, where the model can learn the relationship between words in a sequence without relying on the order of the words. We’ll dive deeper into generative AI models and applications later in this chapter, but it’...

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