Generative AI on GCP: Building Generative AI-powered Apps in GCP
Create a generative AI app on GCP. Learn environment setup, model building with TensorFlow, training loop creation, dockerization of training script, and model deployment to API endpoint.
Skill level
IntermediateTime to complete
Approx. 1 hourCertificate of completion
Yes
About this course
Google Cloud Platform (GCP) has a wide range of powerful generative artificial intelligence (AI) services that can leverage the power of modern AI. Using these services, developers can build powerful applications with GCP, and with the proper use of various technologies, developers new to GCP can gain the knowledge and skills necessary to develop and deploy cutting-edge generative AI applications. In this course, you will create a generative AI-powered app in GCP, beginning with planning and building a generative AI model, GCP environment setup, and Python environment creation. Then you will learn how to build and train a generator and a discriminator with TensorFlow. Next, you will build and run a training loop, and dockerize the training script. Finally, you will deploy your finished model to an application programming interface (API) endpoint and test that model.
Learning objectives
- Discover the key concepts covered in this course
- Provide an overview for building a generative ai model
- Set up a python environment required for training a generative adversarial network (gan)
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. Reviews from learners
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Our learners work at
The Relationship Between the Cloud & AI Explained


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.
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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.