Free Download Generative AI Mastery 2025 Build LLM, RAG & Vision AI Apps
Published 11/2025
Created by Muhammad Yaqoob G
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 46 Lectures ( 8h 17m ) | Size: 7.1 GB
Master LangChain, Llama 3, BGE, Faiss & Milvus with 12+ hands-on projects in LLMs, RAG, Vision AI & Generative Models
What you'll learn
Understand the core concepts of Generative AI, including Transformers, GANs, Autoencoders, and RAG frameworks
Build end-to-end LLM applications using LangChain, Llama 3, BGE, and Faiss for text and document intelligence
Implement Retrieval-Augmented Generation (RAG) systems with vector databases like Milvus for contextual AI chatbots
Develop custom GAN models and use Stable Diffusion for realistic image generation and creative AI workflows
Master text-image similarity search with CLIP embeddings and large-scale vector indexing
Create multimodal AI systems combining text, image, and video understanding using VILA 2.0 and T5
Learn how to train, fine-tune, and deploy Generative AI models for real-world use cases
Understand transformer internals, including multi-head attention, positional embeddings, and feedforward blocks
Explore Autoencoders and Variational Autoencoders (VAE) for denoising, reconstruction, and latent-space learning
Build AI-powered applications like chatbots, video search systems, and intelligent assistants from scratch
Learn to integrate Faiss and Milvus for high-performance vector search and retrieval in production
Develop production-ready AI pipelines, covering embedding generation, inference optimization, and deployment
Gain hands-on experience through 12+ advanced projects blending theory with practical coding
Acquire job-ready AI engineering skills to design, build, and deploy scalable Generative AI solutions
Requirements
Basic Python programming knowledge is required. Know variables, data types, control flow, functions, and basic scripting to follow along with labs.
Windows PC or Laptop with 4GB+ RAM recommended. Ensure Windows OS is installed, there is sufficient disk space for datasets, and essential developer tools ready
A GPU is optional but highly recommended for faster training and real-time experiments; without one, expect much longer training duration and slower performance.
The projects and exercises were developed and tested on Windows systems; guides, scripts, and troubleshooting steps are tailored exclusively for Windows learners.
Description
Step into the world of Generative AI and Large Language Models (LLMs) with this immersive, project-driven course designed to take you from beginner to professional-level mastery. You'll learn to build production-grade AI applications using LangChain, Llama 3, BGE, Faiss, and Milvus - the same frameworks that power real-world enterprise and research-grade AI systems.The course begins with a deep dive into the core concepts of Transformers, GANs, and Embeddings, helping you understand how generative models process and generate human-like content. You'll then explore Retrieval-Augmented Generation (RAG), vector databases, and multimodal AI to create powerful, context-aware, and intelligent solutions for text, image, and video understanding.Through 12+ guided projects, you'll build AI chatbots, document retrieval systems, image generators, similarity search engines, and video retrieval applications using cutting-edge models like VILA 2.0 and T5. Every module focuses on hands-on learning, ensuring you can confidently apply each technique to real-world use cases.By the end of this course, you'll master the full Generative AI pipeline - from data embedding, model chaining, fine-tuning, and optimization to scalable deployment across edge, cloud, or hybrid environments.Whether you're an AI engineer, Python developer, data scientist, or tech innovator, this course equips you with the knowledge, confidence, and practical experience to design, build, and deploy next-generation LLM and Vision AI systems from scratch.
Who this course is for
This course is designed for learners who want to go beyond theory and gain hands-on mastery of Generative AI tools, models, and real-world applications.
AI & ML Beginners who have basic Python knowledge and want to quickly step into the world of Generative AI with structured, practical guidance.
Data Scientists & ML Engineers looking to strengthen their skills in autoencoders, GANs, transformers, retrieval-augmented generation (RAG), and diffusion models.
Software Developers interested in integrating generative AI into apps with FastAPI, Tkinter, LangChain, Milvus/FAISS, and Docker deployments.
Researchers & Students who want to deeply understand how models like GPT, BERT, LLaMA, and Stable Diffusion work internally and apply them in projects.
Tech Enthusiasts eager to explore generative applications such as image denoising, text-to-image generation, AI-powered search, face recognition, video similarity, and multimodal tasks.
Entrepreneurs & Innovators planning to build AI-driven products in fields like chatbots, recommendation systems, creative design, surveillance, and smart automation.
No prior deep learning expertise is strictly required, but familiarity with Python and basic ML concepts (supervised vs. unsupervised learning) will help you get the most out of this course.
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