Generative AI on GCP: Empowering Machine Language Workflows with Vertex AI

Learn Vertex AI on GCP: end-to-end ML workflows, model deployment, training, data preparation, feature engineering, and evaluation for effective AI solutions.

  • Skill level

  • Time to complete

    Approx. 2 hours
  • Certificate of completion


About this course

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 (AI). A main component of that toolbox is Google's Vertex AI platform, which can aid organizations in streamlining machine learning (ML) workflows and deliver better machine learning models. In this course, you'll be introduced to Vertex AI, beginning with an overview of its features, model deployment, and end-to-end workflow. Then you'll explore pros and cons of Vertex AI, how it can be used to accelerate development, and model selection, training, and evaluation considerations. Finally, you'll learn about Vertex AI integration, data preparation, feature engineering, model evaluation, and Vertex AI success stories.

Learning objectives

  • Discover the key concepts covered in this course
  • Outline the fundamentals of vertex ai and its role in the machine learning (ml) life cycle
  • Identify key features of vertex ai, including mlops, automl, custom training, and interfaces

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.

Generative AI on GCP: Empowering Machine Language Workflows with Vertex AI course reviews

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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.  

Continue reading

Join over 50 million learners and start Generative AI on GCP: Empowering Machine Language Workflows with Vertex AI today!


Unlock additional features with a paid plan

  • Portfolio projects

    Create professional projects you can share with recruiters to showcase your skills and experience.
  • Job-readiness checker

    Evaluate how well you meet the requirements for any job description based on your skills and experience.
  • Certificate of completion

    Earn a document you can share with your network to prove that you’ve completed this course.