llm
AI and LLM engineering
LLM basics, prompting, RAG, agents and evals
7 topics 8 sections Claude Developer Platform (2026-09) beginner → intermediate
recommended path AI-native developer
milestone 1 of 5 0 of 26 done
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01 · LLM basics
6 topics Claude API Build reliable Claude Messages API requests, content-block parsers, streams, and tool loops with safe retry boundaries. intermediate 13 min Hugging Face Use the Hub to manage model artifacts and Transformers Pipeline and AutoClass for reproducible, secure local inference. intermediate 13 min LLM application basics Build your first LLM feature with an explicit input contract, output validation, an evaluation set, and a safe model boundary. beginner 15 min Local large language models Select, run, and evaluate LLMs on your own hardware while handling quantization, context memory, streaming, and service boundaries. intermediate 13 min Natural language processing Turn language into testable classification, labeling, and retrieval tasks without losing semantics, offsets, or evaluation integrity. intermediate 15 min OpenAI API Build with the Responses API, parse typed output, manage conversations and streams, and handle keys, status, and retry boundaries correctly. intermediate 14 min