개발자를 위한 AI
LLM API, 프롬프트, RAG, 에이전트로 만들어 보세요.
Large language models can now write, summarize, translate, classify and even call your own code, and adding one to an app takes a single HTTP request. This track is for developers who can already program. You learn how models really work (tokens, context windows, next-token prediction and why they can be confidently wrong), call the Anthropic Messages API correctly, write prompts that return reliable JSON, stream answers and keep costs under control. Then you build real features: tool use, retrieval-augmented generation with embeddings, agents with guardrails and MCP, and the safety and testing habits that keep all of it trustworthy.
Every request is shown exactly as it travels over the network.
- 레슨
- 14
- 시간
- 2시간
- 난이도
- 중급
이 코스의 레슨은 당분간 영어로 제공돼요.
- 브론즈 도전 가능
- 실버 도전 가능
- 골드 잠김
실력을 증명할 준비됐나요?
브론즈, 실버, 골드 세 가지 시험이 기다리고 있어요.
이 코스를 마치면 할 수 있는 것
- Explain tokens, context windows and sampling, and why models can be confidently wrong
- Call the Anthropic Messages API safely from a server, with streaming
- Write prompts that return JSON, and validate it before you trust it
- Control cost and limits with token budgets, caching and retries
- Build tool use, RAG and a small agent with guardrails
- Defend against prompt injection and measure quality with evals
여정
1 챕터 1Working with models
How LLMs work, your first API call, prompting, streaming and costs.
0 / 52 챕터 2Building real features
Tool use, retrieval, agents, safety and evaluation.
0 / 53 챕터 3Next level
Structured outputs, images and documents, deeper evals and your own MCP server.
0 / 4