Large Language Models (LLMs) Explained From Zero to AI Apps

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Large Language Models (LLMs) Explained From Zero to AI Apps
Published 9/2026
Created by Medhat Gadallah
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 16 Lectures ( 3h 51m ) | Size: 2.5 GB

Master LLMs, Transformers, Tokens, Embeddings, RAG, and AI Application Development from the Fundamentals
What you'll learn
Understand how Large Language Models (LLMs) work, from tokens and embeddings to Transformers and AI applications.
Explain how modern AI systems process language using tokenization, embeddings, neural networks, and attention mechanisms.
Understand how LLMs are trained, fine-tuned, evaluated, and deployed in real-world applications.
Build a strong foundation for creating AI applications using LLMs, RAG systems, APIs, and modern AI tools.
Understand practical concepts behind ChatGPT-style applications, including context windows, prompting, retrieval, and AI agents.
Develop the knowledge needed to move from AI beginner to confidently working with Large Language Models and AI engineering concepts.
Requirements
No prior AI or machine learning experience is required. This course starts from the fundamentals and builds your understanding step by step.
Basic computer skills and curiosity about Artificial Intelligence are enough to get started.
A willingness to learn technical concepts through simple explanations and practical examples.
Programming experience is helpful but not required, as the course focuses on understanding concepts before implementation.
Description
This course contains the use of artificial intelligence.
Have you ever wondered how ChatGPT and modern AI assistants actually work?
This course provides a complete beginner-friendly journey into the world of Large Language Models (LLMs) and Generative AI. You will learn the core concepts behind today's most powerful AI systems and understand how they transform human language into intelligent responses.
Starting from the fundamentals, you will explore how Large Language Models process text using tokens, tokenization, embeddings, neural networks, Transformers, and attention mechanisms. You will understand how AI models learn patterns, generate responses, and represent meaning mathematically.
Throughout the course, you will discover the complete lifecycle of modern LLMs
• How text becomes tokens and token IDs
• How embeddings allow AI systems to understand relationships and meaning
• How neural networks and Transformers power modern language models
• How attention mechanisms help models focus on important information
• How LLMs are trained, evaluated, and improved
• How context windows, prompting, and token efficiency affect AI applications
• How Retrieval-Augmented Generation (RAG) connects LLMs with external knowledge
• How modern AI applications are built using LLM technologies
This course focuses on understanding the technology behind AI applications, not just using AI tools. You will build the mental model needed to confidently explore AI engineering, RAG systems, AI agents, and LLM-powered applications.
By the end of this course, you will have a strong foundation in Large Language Models and understand the concepts used behind ChatGPT-style applications.
Who is this course for?
• Beginners who want to understand how modern AI works
• Developers preparing to build AI-powered applications
• Software engineers exploring Generative AI and LLM technologies
• Students and professionals entering the AI field
• Anyone who wants to move beyond using AI tools and understand the technology behind them
No advanced mathematics or machine learning background is required. The course starts from the basics and gradually builds your understanding step by step.
Join the course and start your journey into the technology shaping the future of Artificial Intelligence.
Who this course is for
Beginners who want to understand how ChatGPT and modern Large Language Models work.
Developers who want a strong foundation before building AI-powered applications.
Software engineers, data professionals, and technology enthusiasts entering the AI field.
Students and professionals who want to understand Generative AI, LLMs, RAG, and AI application architecture.
Anyone who wants to move beyond using AI tools and understand the technology behind them.
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