Large Language Models: From Fundamentals to Production

Master Large Language Models: From Theory to Production

This comprehensive course takes you on a deep dive into the world of Large Language Models (LLMs). Whether you're a developer, data scientist, or technical leader, you'll gain the knowledge and practical skills needed to understand, build with, and deploy LLM-powered applications.

What You'll Learn

• Core Foundations — Understand transformer architecture, attention mechanisms, and how modern LLMs work under the hood
• Prompt Engineering — Master the art and science of crafting effective prompts for any use case
• RAG Systems — Build retrieval-augmented generation pipelines that ground LLMs in your own data
• Fine-Tuning — Customize models with LoRA, QLoRA, and modern parameter-efficient training techniques
• AI Agents — Design autonomous agents with tool use, function calling, and multi-agent orchestration
• Production Deployment — Ship LLM applications with proper safety guardrails, monitoring, and cost controls

Prerequisites

• Basic Python programming knowledge
• Familiarity with machine learning concepts (helpful but not required)
• Curiosity and willingness to experiment!

Course Format

6 modules with structured lessons covering theory, practical examples, and best practices. Each section builds on the previous one, taking you from fundamentals to production-ready skills.