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?


您将学到什么
Describe generative-AI-based application types and use cases.
Describe how to build prompt templates to improve model response quality in applications.
Describe the subsystems of RAG-capable architectures for generative AI applications on Google Cloud.
Build an LLM and RAG-based chat application.
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3 项作业
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该课程共有6个模块
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.
涵盖的内容
1个作业5个插件
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.
涵盖的内容
1个作业5个插件
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.
涵盖的内容
1个视频1个应用程序项目
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.
涵盖的内容
1个作业6个插件
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.
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1个应用程序项目
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Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
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