AI & LLM Engineering Mastery: GenAI, RAG Complete Guide | Udemy [02/2025]
English | Size: 16.21 GB
Genre: eLearning[/center]
From Fundamentals to Advanced AI Engineering - Fine-Tuning, RAG, AI Agents, Vector Databases & Real-World Projects
What you'll 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.
Become an AI Engineer and master Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), AI agents, and vector databases in this comprehensive hands-on course.
Whether a beginner or an experienced developer, this course will take you from zero to hero in building real-world AI-powered applications.
This course combines deep theoretical insights with hands-on projects, ensuring you understand AI model architectures, development and optimization strategies, and practical applications.
What You'll Learn:
Deep Learning & Machine Learning Foundations
Understand neural networks, activation functions, transformers, and the evolution of AI.
Learn how modern AI models are trained, optimized, and deployed in real-world applications.
Master Large Language Models (LLMs) & Transformer-Based AI
Deep dive into OpenAI models, and open-source AI frameworks.
Build and deploy custom LLM-powered applications from scratch.
Retrieval-Augmented Generation (RAG) & AI-Powered Search
Learn how AI retrieves knowledge using vector embeddings, FAISS, and ChromaDB.
Implement scalable RAG systems for AI-powered document search and retrieval.
LangChain & AI Agent Workflows
Build AI agents that autonomously retrieve, process, and generate information.
Fine-Tuning LLMs & Open-Source AI Models
Fine-tune OpenAI, and LoRA models for custom applications.
Learn how to optimize LLMs for better accuracy, efficiency, and scalability.
Vector Databases & AI-Driven Knowledge Retrieval
Work with FAISS, ChromaDB, and vector-based AI search workflows.
Develop AI systems that retrieve and process structured & unstructured data.
Hands-on with AI Deployment & Real-World Applications
Build AI-powered chatbots, multimodal RAG applications, and AI automation tools.
Who Should Take This Course?
Aspiring AI Engineers & Data Scientists - Looking to master LLMs, AI retrieval, and search systems.
Developers & Software Engineers - Who want to integrate AI into their applications.
Machine Learning Enthusiasts - Seeking a deep dive into AI, GenAI, and AI-powered search.
Tech Entrepreneurs & Product Managers - Wanting to build AI-driven SaaS products.
Students & AI Beginners - Who need a structured, step-by-step path from beginner to expert.
Course Requirements
No prior AI experience required - the course takes you from beginner to expert.
Basic Python knowledge (recommended but not required - Python Fundamentals Included in the course).
Familiarity with APIs & JSON is helpful but not mandatory.
A computer with internet access for hands-on development.
Why Take This Course?
Comprehensive AI Training: Covers LLMs, RAG, AI Agents, Vector Databases, Fine-Tuning.
Hands-On Projects: Every concept is reinforced with real-world AI applications.
Up-to-Date & Practical: Learn cutting-edge AI techniques & tools used in top tech companies.
Zero to Hero Approach: Designed for absolute beginners & experienced developers alike.
Master AI Engineering and become an expert in GenAI, LLMs, and RAG today.
Who this course is for:
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.
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