LLM Engineering Foundations
Most developers know chat. This module shows how developers use LLMs inside real applications: calling APIs, shaping outputs, and building reliable interactions. You’ll learn how to think about LLMs as an engineering component — not a toy.
Prompting Patterns Developers Actually Use
Prompting isn’t magic — it’s a set of repeatable patterns. You’ll learn what works, what breaks, and how teams keep prompts consistent across features, so your prompt approach is reusable and improvable over time.
Frameworks & Building Blocks (LangChain + Alternatives)
There are many frameworks. You’ll learn the “why” behind them and the building blocks they provide — so you can understand the ecosystem without getting trapped in it. You’ll be able to evaluate tools/frameworks and choose what fits your project.
RAG + Vector Search (The Big Picture)
Developers hear “RAG” everywhere. You’ll learn what it is, why it exists, and what a typical RAG system looks like end-to-end — at a practical level. You’ll understand how teams connect documents to AI systems, and when RAG is (and isn’t) the right approach.
Agents & Tool Calling (Beyond Chatbots)
Agents are about workflows: taking a goal, using tools, and producing results. You’ll learn the core concepts and patterns — enough to build a working mental model and start experimenting safely. You’ll understand how tool-using agents work and how they fit into real software systems.
The Modern AI Stack: Models, MCP, and Shipping Basics
The AI world moves fast. You’ll learn the landscape: local vs hosted models, what MCP is (and where it fits), and the practical basics teams think about when shipping AI features. You’ll leave with a clear “what matters” framework for better decisions and deeper learning later.
Multimodal AI (Images + Audio)
AI isn’t only text anymore. You’ll learn how modern apps use image and audio capabilities and what developers should understand before integrating them into real products. You’ll be able to recognize the main multimodal use cases and design where these features fit in your own applications.
Staying Current (Tools, Trends, and What to Learn Next)
New models and frameworks drop constantly. You’ll learn how to evaluate what’s real vs hype, and how to choose what to learn based on the kinds of systems you want to build. You’ll leave with a practical learning path and the confidence to keep up without getting overwhelmed.
