> ## Documentation Index
> Fetch the complete documentation index at: https://genai.codewithsiva.dev/llms.txt
> Use this file to discover all available pages before exploring further.
# GenAI Foundations
> Master the core concepts and practical essentials of Generative AI and Large Language Models
Welcome to the **Generative AI Foundations** module. This module provides a comprehensive introduction to Large Language Models (LLMs), covering how they are built, how they work conceptually, and how to start building applications with them.
## πΊοΈ Module Overview
This module is designed to bridge the gap between AI theory and software development:
```mermaid theme={null}
graph TD
A["Conceptual Architecture
(Transformers, Attention, Tokens)"]
--> B["Model Landscapes
(Open vs. Closed, Local vs. Cloud)"]
--> C["API Integrations & SDKs
(Programmatic Calls & Chat Sessions)"]
--> D["Practical Capstone
(Build a CLI Chatbot from scratch)"]
```
## π Module Curriculum & Roadmap
Explore the sections in this module using the cards below:
Learn the historical shift from rule-based expert systems to statistical machine learning, deep learning, NLP sequential models, and the transformer/attention revolution.
Compare encoder-only, decoder-only, and seq-to-seq models. Explore key components like embeddings, positional encodings, and self-attention mechanisms.
Understand what an LLM is, why they are called Large, the training vs. inference lifecycles, and how autoregressive next-token prediction works.
Review input/output token pricing, model selection strategies, types of applications built with LLMs, and the modern GenAI application stack.