PHMultimodal Genai Rag Apps - English Version
Published 9/2025
Created by Coursat.ai Dr. Ahmad ElSallab
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Expert | Genre: eLearning | Language: English | Duration: 43 Lectures ( 5h 59m ) | Size: 2 GB
Build Next-Gen RAG Systems - Harness the Power of Multimodal GenAI
What you'll learn
Build RAG models to augment LLM knowledge
Build multi-modal apps with different LLM models including Text, Speech and Image
Understand the different RAG components and Design Patterns
Design RAG systems and identify the best design choices for each application
Requirements
Python
NLP
Transformers
Generative AI Foundations
Description
Disclaimer: The audio narration in this course is AI-generated, based on human-written scripts and human-designed slides. The use of AI narration is to improve clarity for learners, while all instructional content remains instructor-created.This is Part 2 of the Practical GenAI Sequel.The goal of this sequel is to prepare you to become a professional GenAI engineer or developer. We'll start from the ground up in the world of LLMs and GenAI, moving from the basics all the way to building real, production-level applications.The spirit of this sequel is entirely hands-on. Every concept is demonstrated with code-based examples, and you'll work on step-by-step projects in Python, Google Colab, and Streamlit.By the end of this course, you will have built a wide range of applications, including:A ᑕᕼᗩTGᑭT cloneA MidJourney-style image generatorChat with Your Data appYouTube Assistant appAsk YouTube Video appStudy Mate appRecommender systemImage Description app with GPT-Vímágé Generation apps with DALL·E and Stable DiffusionVideo Commentator app using Whisper...and many more.We'll explore prompt engineering techniques and apply them to create custom applications that go beyond what ᑕᕼᗩTGᑭT can do. Along the way, we'll use OpenAI APIs, LangChain, and other powerful tools, all deployed with Streamlit, chosen for its simplicity and Python-friendly design.You'll also learn to work with different GPT models-both proprietary (OpenAI) and open-source (like LLaMA and Mixtral on Hugging Face)-to build advanced apps such as document chatbots, YouTube video assistants, state-of-the-art recommender systems, and automatic video commentators or translators.This course also introduces multimodality:Text with GPT-3.5 and GPT-4Images with GPT-V and DALL·EVoice with WhisperFinally, we'll dive into feeding AI with custom data-knowledge not available on the internet or to open models like ᑕᕼᗩTGᑭT-and explore advanced, cutting-edge topics such as RAG (Retrieval-Augmented Generation) systems and LLM Agents.Disclaimer: The audio narration in this course is AI-generated, based on human-written scripts and human-designed slides. The use of AI narration is to improve clarity for learners, while all instructional content remains instructor-created.
Who this course is for
Entrepreneurs that want to build new ideas with GenAI
Developers that integrate AI capabilities in their apps
GenAI engineers/developers