Create Generative AI Apps on Google Cloud

Overview

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Generative AI applications can create new user experiences that were nearly impossible before the invention of large language models (LLMs). As an application developer, how can you use generative AI to build engaging, powerful apps on Google Cloud? In this course, you'll learn about generative AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs. You'll learn about a production-ready architecture that can be used for generative AI applications and you'll build an LLM and RAG-based chat application.

Syllabus

Generative AI Applications

In this module, you learn about generative AI applications, and types of applications that can use the power of generative AI. You also learn about foundation models provided by Google, and challenges that exist when using generative AI in your applications.

Prompts

In this module, you learn about generative AI prompts. A prompt is a natural language request submied to a language model to request a response back. You can design your prompts to improve the results being returned from a model.

Get Started with Vertex AI Studio

In this module, you experiment with Vertex AI Studio, which provides tools to rapidly prototype, tune models with your own data, and seamlessly deploy to applications. You explore multimodal capabilities of Gemini, design prompts, and generate conversations.

Retrieval Augmented Generation (RAG)

In this module, you learn how to improve the accuracy of foundation models. You learn about retrieval augmented generation, or RAG, a technique for grounding a foundation model with external sources of knowledge. You'll also see an example RAG-capable generative AI solution architecture on Google Cloud.

Build an LLM and RAG-based Chat Application

In this module, you build a chat application that uses large language models (LLMs) and retrieval augmented generation (RAG) to create engaging and informative conversations.