Deep Dive into LLMs: Complete Technical Lecture on Large Language Models (2026 Explained)

In this deep technical lecture, we explain Large Language Models (LLMs) — the core technology behind modern AI systems like ChatGPT, Gemini, Claude, and more. This full 1.5-hour deep dive is designed for engineers, developers, and advanced learners who want to understand how LLMs actually work, including: 🔹 What large language models are and how they differ from classic language models 🔹 The Transformer architecture and attention mechanisms 🔹 Tokenization, embeddings, and context windows 🔹 How LLMs are trained — from data pipelines to self-supervised pretraining 🔹 Inference workflows and engineering challenges at scale 🔹 Alignment, evaluation, and ethical considerations Whether you’re a software engineer, AI researcher, or serious student of machine learning, this lecture breaks down the engineering and system design behind LLMs — not just surface-level concepts. We go beyond basics into the mechanics and design of modern AI systems that power today’s generative models. 📌 Timestamps: 00:00:00 Introduction of this Class 00:02:19 What is LLM? 00:06:15 Pretraining Dataset(Internet - Fineweb) 00:20:28 Tokenisation Process 00:33:06 Neural Network Training 00:46:27 Internals of Neural Networks 00:49:57 Inference 00:52:42 Base Model- Lama 3B (after pre-training) 00:55:49 Post-Training, Supervised Fine Tuning (Human-conversation Dataset) 01:04:20 Hallucinations 01:12:23 Model needs more tokens 01:15:28 Jagged Intelligence 01:17:50 Reinforcement Learning(Deepseek R1) 01:21:46 Outro & Grand Summary 👉 Don’t forget to like, subscribe, and hit the bell for more deep technical lectures on AI, system design, and modern software engineering. #LLM #Transformers #AIEngineering #DeepLearning #ChatGPT #MachineLearning