中级
Prompt Engineering
从 generative AI 中获得可靠的结果。学习 large language models 如何生成文本、每个好 prompt 背后的五条原则、few-shot 与 structured output、function calling、retrieval-augmented generation、自主 agents,以及 diffusion models 如何把 prompts 变成图像。最后你将把文本、图像和 agents 接线成一个可运行的应用。
10 节5.8h 实操11 种语言
免费开始学习Prompt Engineering 课程共 10 节,按顺序
- 130 分钟
提示工程的五项原则
Giving directionSpecifying formatProviding examplesEvaluating qualityDividing labor - 230 分钟
大语言模型如何生成文本
Tokens and tokenizationNext-token predictionTemperature and top-p samplingContext windowWhy models hallucinate - 335 分钟
文本生成的标准实践
Prompt formatting and delimitersSystem, user, and assistant rolesFew-shot promptingParsing structured output like JSON - 435 分钟
Prompt Template 与 Function Calling
Prompt templates with variablesSeparating template from dataFunction calling and tool schemasReading a tool call and returning a result - 540 分钟
向量数据库与检索增强生成
Embeddings and vector similarityChunking documentsVector databases and nearest-neighbor searchRetrieval-augmented generationGrounding answers with citations - 640 分钟
Autonomous Agents:memory 与 tools
The agent loop of reason, act, observeGiving an agent toolsShort-term and long-term memoryStopping conditions and guardrails - 730 分钟
Diffusion 模型如何生成图像
Diffusion as iterative denoisingText conditioning of the imageSeeds and reproducibilitySampling steps and guidance scale - 835 分钟
图像生成的标准实践
Prompt structure of subject, medium, style, and lightingArt styles and artist or era modifiersComposition and camera modifiersNegative prompts and aspect ratio - 935 分钟
进阶图像技巧:inpainting、outpainting 与 ControlNet
Image-to-image generationInpainting with masksOutpainting to extend a canvasControlNet for pose, depth, and edge guidance - 1040 分钟
构建 AI 驱动的应用
Composing text, images, and agents into a workflowOrchestration and chaining stepsEvaluation and guardrailsCost, latency, and failure handling
用你的语言学习 Prompt Engineering
每一节课、测验和导师回复都以你的语言显示。AI 导师会用你提问的语言来回答。
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