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Learning Guide Overview

Welcome to the ClientAI Learning Guide! This comprehensive resource is designed to teach you the fundamentals of Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG), and Machine Learning Engineering using practical examples with ClientAI.

🚧 Under Construction

This learning guide is currently under active development. While we're working hard to create comprehensive content, some sections may be incomplete or pending. We appreciate your patience and encourage you to check back regularly for updates.

What You'll Learn

This guide will take you through:

  • LLM Fundamentals: Understanding how large language models work, their capabilities, and how to effectively use them through ClientAI
  • Agent Development: Learning to build intelligent AI agents that can reason, use tools, and solve complex tasks
  • Retrieval Systems: Implementing RAG systems to give your applications access to custom knowledge
  • Production Engineering: Deploying and managing LLM applications in production environments

Tip

Looking for Quick Start Instructions?
This Learning Guide focuses on building a comprehensive understanding of theoretical concepts and practices, you might want to check our Usage Guide to get up and running with ClientAI.

Prerequisites

To get the most out of this guide, you should have:

  • Basic Python programming knowledge
  • ClientAI installed in your environment
  • Basic understanding of machine learning concepts (helpful but not required)

Complete Curriculum

Fundamentals

  1. LLM Basics 🚧 Coming Soon

    • Learn the fundamentals of Large Language Models, including their architecture, capabilities, and key concepts through hands-on practice with ClientAI.

  2. Prompt Engineering 🚧 Coming Soon

    • Master effective prompt design techniques, from basic principles to advanced templates, with practical ClientAI implementation examples.

Working with Agents

  1. Agent Fundamentals 🚧 Coming Soon

    • Understand AI agents and their architectures while building your first reasoning agents using ClientAI's framework.

  2. Tools and Reasoning 🚧 Coming Soon

    • Create sophisticated tool-using agents with automated selection and custom tools for complex problem-solving tasks.

Retrieval and Knowledge

  1. Introduction to RAG 🚧 Coming Soon

    • Explore the basics of Retrieval-Augmented Generation and build your first RAG system with vector databases and embeddings.

  2. Advanced RAG 🚧 Coming Soon

    • Master advanced retrieval strategies and optimization techniques for building sophisticated document processing systems.

MLOps and Engineering

  1. Deployment Patterns 🚧 Coming Soon

    • Learn essential deployment architectures and strategies for scaling LLM applications in production environments.

  2. Best Practices 🚧 Coming Soon

    • Master production-grade practices for testing, security, and optimization of LLM applications.

Applied Projects

  1. Building a Production Chatbot 🚧 Coming Soon

    • Build a complete, production-ready chatbot from design to deployment with advanced context management.

  2. Document Assistant 🚧 Coming Soon

    • Create a comprehensive document Q&A system using RAG, with optimized retrieval and tool integration.

How to Use This Guide

The guide is structured progressively, building from fundamental concepts to advanced implementations. To better learn:

  1. Read the theoretical explanations and see how they translate to code
  2. Run the practical examples, experiment with them, and modify parameters
  3. Consult the Usage Guide or API documentation to understand features in depth
  4. Review the Examples for additional learning material
  5. Create your own projects! Building and breaking things is the best way to learn

Contributing

This guide is open to community contributions! If you'd like to help improve or expand the learning materials:

  • Check our Contributing Guidelines
  • Submit issues or pull requests for improvements
  • Share your feedback and suggestions with the community

You'll soon be able to tart your learning journey by heading to the LLM Basics section!