Building with LLMs

Using the OpenAI API with Python

Building Your First AI App with the Claude API: Complete Beginner's Guide

Learn to build a real AI-powered customer support assistant from scratch using Anthropic's Claude API. No prior AI experience required—just practical Python skills and clear explanations.

OpenAI vs Anthropic vs Open Source: Choosing the Right LLM

Structured Output: Getting JSON, Tables, and Code from LLMs

Master the techniques to get reliable JSON, formatted tables, and executable code from any large language model instead of parsing unpredictable text responses.

Function Calling and Tool Use with LLMs: Building Intelligent Agents

Learn to give LLMs access to external tools and data sources, transforming them from text generators into powerful problem-solving agents that can interact with real systems.

Building a Production Document Q&A System with Vector Embeddings

Learn to build a scalable document Q&A system using embeddings and RAG. Covers advanced chunking, vector search optimization, prompt engineering, and production deployment with real-world regulatory compliance examples.

Building a Document Q&A System with Embeddings: A Complete Beginner's Guide

Learn to build an AI-powered document Q&A system from scratch using embeddings and language models. No prior AI experience required—just practical Python skills and clear explanations.

Building Streaming AI Interfaces: Real-Time Response Delivery

Learn to build responsive AI applications that stream tokens in real-time, creating conversational experiences that engage users from the first word.

Streaming Responses and Real-Time AI Interfaces

Cost Optimization: Token Counting, Caching, and Model Selection for LLMs

Master practical techniques to reduce your LLM API costs by 60-80% while maintaining quality. Learn token tracking, intelligent caching, and strategic model selection with hands-on examples.

Testing and Evaluating LLM Applications: A Comprehensive Guide to Quality Assurance

Master the art of testing non-deterministic LLM applications with rule-based validation, model-based evaluation, automated testing pipelines, and production monitoring strategies that catch problems before they impact users.

Building AI Workflows with LangChain and LlamaIndex

Deploying LLM Applications: API Design and Infrastructure

Learn to build production-ready LLM applications with proper API design, infrastructure scaling, cost management, and monitoring. From local development to cloud deployment.