Implementing RAG with multimodal data

From Fundamentals to Advanced AI Engineering – Fine-Tuning, RAG, AI Agents, Vector Databases & Real-World Projects

Created by: Paulo Dichone | Software Engineer, AWS Cloud Practitioner & Instructor
Android, Flutter, AWS, Best Selling Instructor

What Will I Learn?

• Master the architecture and workflow of a RAG system for processing PDFs and multimodal data.
• Master the Fundamentals of AI, Machine Learning and Deep Learning (Basics)
• Master LangChain tools, frameworks, and workflows, including embedding techniques and retrievers.
• Fine-tuning models with OpenAI, LoRA, and other techniques to customize AI responses.
• Develop AI-driven applications with advanced RAG techniques, multimodal search, and AI agents for real-world use cases.

Requirements

• Basics of Programming - Python Fundamentals INCLUDED

Target audience

• Developers looking to implement AI-powered document search and retrieval.
• Tech Entrepreneurs & Product Managers who want to build AI-driven applications.
• Students & Researchers exploring the practical applications of LLMs and AI-driven automation.