Generative AI on GCP: An Introduction

Dive into generative AI on Google Cloud Platform. Learn AI development, GCP advantages and machine learning services, image generation, NLP, and more.

  • Skill level

  • Time to complete

    Approx. 2 hours
  • Certificate of completion

  • Prerequisites


About this course

Generative artificial intelligence (AI) has taken the world by storm. Chatbots, photo creation, document writing, and other practical applications are everywhere, and they're gaining in popularity and sophistication. Google Cloud Platform (GCP) has a broad range of powerful generative AI tools that can be used to leverage the power of modern artificial intelligence. In this course, you'll be introduced to generative AI, beginning with GCP and its generative AI offerings. You will discover the advantages and disadvantages of generative AI and features of GCP machine learning (ML). Then you'll learn about the generative AI life cycle, image generation, natural language processing (NLP), and best practices for developing generative AI. Finally, you'll explore GCP privacy, security, and compliance considerations, monitoring and logging with GCP, and some real-world generative AI use cases.

Learning objectives

  • Discover the key concepts covered in this course
  • Outline the fundamentals of generative artificial intelligence (ai) and its applications in the cloud
  • Provide an overview of the generative ai services provided by google cloud platform (gcp)

How it works

Expert-led videos

In this course, you'll watch videos created by industry-leading experts for some of the biggest tech companies in the world. They'll cover key concepts, go through sample applications, prepare you for industry certifications, and more. Watch on any device — whenever and wherever you want — to learn at your own pace.

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The Relationship Between the Cloud & AI Explained

Cory Stieg
May 1, 2024

As AI finds its way into so many aspects of our lives, it’s even more important to understand the infrastructure that powers this valuable tool. That includes the cloud, which is a big part of how AI apps are deployed and scaled.  

Cloud computing basically refers to internet-delivered services like servers, storage, databases, networks, software, and analytics. The cloud provides computational power and ample data storage that’s needed to train, develop, and deploy cutting-edge AI models.  

If you’re looking for a way to get started with cloud technology, we recently launched a collection of free cloud courses. These courses provide you with foundational knowledge in core cloud providers including Microsoft Azure, Amazon Web Services, Google Cloud, and CompTIA Cloud Essentials+. With these cloud courses, you have the option to dive in and explore for free before committing to a cloud certification program. They’re also an excellent way to complement the in-demand AI and coding skills that you’re already learning. 

Ahead, we’ll break down the relationship between cloud computing and AI with insight from Michael Shannon, a Senior Analyst in Tech and Dev at Skillsoft, who developed the curriculum for many of our cloud courses.  

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