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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.

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.


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

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.

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.

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.



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


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.