Multimodal RAG: AI Search & Recommender Systems with GPT-4

🌟 Course Title: Mastering Multimodal RAG: Build AI-Powered Search & Recommender Systems with GPT-4, CLIP, and ChromaDB

Course Instructor: Paulo Dichone | Software Engineer, AWS Cloud Practitioner & Instructor

Course Headline:

Unlock the full potential of AI-driven search and recommender systems with our comprehensive online course. By leveraging cutting-edge tools like GPT-4, CLIP, and ChromaDB, you'll learn to build sophisticated Multimodal Retrieval-Augmented Generation (RAG) systems that blending text and image data for advanced information retrieval. 🧠🚀

Course Description:

Are you ready to dive into the cutting-edge world of AI-powered search and recommender systems? This course will guide you through the process of building Multimodal RAG systems that combine text and image data for advanced information retrieval and recommendations.

In this hands-on course, you'll learn how to leverage state-of-the-art tools such as GPT-4, CLIP, and ChromaDB to build AI systems capable of processing multimodal data—enhancing traditional search methods with the power of machine learning and embeddings.

What You’ll Learn:

• ✅ Master Multimodal RAG: Understand the concept of Retrieval-Augmented Generation (RAG) and how to implement it for both text and image-based data.
• ✅ Build AI-Powered Search & Recommendation Systems: Construct search engines and recommender systems that can handle multimodal queries using powerful AI models like GPT-4 and CLIP.
• ✅ Utilize Embeddings for Cross-Modal Search: Gain practical experience generating and using embeddings to enable search and recommendations based on text or image input.
• ✅ Develop Interactive Applications with Streamlit: Create user-friendly applications that allow real-time querying and recommendations based on user-provided text or image data.

Key Technologies You'll Work With:

• GPT-4: A cutting-edge language model that powers the AI-driven recommendations.
• CLIP: An advanced AI model for generating image and text embeddings, making it possible to search images with text.
• ChromaDB: A high-performance vector database that enables fast and efficient querying for multimodal embeddings.
• Streamlit: A simple yet powerful framework for building interactive web applications.

No prior experience with multimodal systems? No problem! 🚫

This course is designed to make advanced AI concepts accessible, with detailed, step-by-step instructions that guide you through each process—from generating embeddings to building complete AI systems. Basic Python knowledge and a curiosity for AI are all you need to get started.

Enroll today and take your AI development skills to the next level by mastering the art of multimodal RAG systems! 🎓✨

Join us on this journey to explore the intersection of machine learning, natural language processing, and computer vision. From generating embeddings to creating interactive applications, you'll gain hands-on experience with the most powerful tools in AI today. Ready to be at the forefront of AI innovation? Let's embark on this exciting learning path together!