Explore RAG with Google Gemini. Learn its architecture, APIs, and capabilities. Build hands-on applications, integrate LangChain, and create a customer service assistant with multimodal AI prompts.

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Unlock the power of RAG with Google Gemini in this hands-on course. Learn about Google Gemini, a family of multimodal large language models (LLMs), and its cutting-edge applications developed by Google.

Explore Gemini’s evolution, architecture, and APIs to understand its unimodal and multimodal AI content generation capabilities. Dive into retrieval-augmented generation (RAG) techniques using Gemini and LangChain. Implement RAG applications to generate text and image responses from external knowledge sources and provide prompts.

In the final project, create a customer service assistant application with a Streamlit interface, integrating Gemini’s multimodal AI capabilities for image-to-text and text-to-text prompts. After completing this course, you’ll have the expertise to build real-world RAG applications with Google Gemini.

Building Multimodal RAG Applications with Google Gemini

Learn how to generate textual content with multimodal prompts using real-world examples with Gemini.

Text and Image-to-Text Generation

Getting Started

Content Generation Using Gemini Models

Building RAG Applications with Google Gemini

Customer Service Assistant—Multimodal RAG Interface

Wrapping Up

Text and Image-to-Text Generation