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所在平台: Udemy |
课程主页: https://www.udemy.com/course/prompt-engineering-ps/
课程评论：没有评论
**课程名称：** 提示工程 (Prompt Engineering) **课程概述：** 本课程将重点介绍提示工程的三个关键要素：数据 (data)、语境 (context) 和动词 (verb)。 随着人工智能 (AI) 工具和应用的普及，有效的语境设定变得至关重要。与人类不同，AI 应用没有记忆能力，无法像人一样自行连接信息并给出恰当的响应。为了模拟人类的反应，AI 软件和工具需要明确的语境和示例数据。 **举例说明：** * **“请写一个关于夏天的故事。”** 这个提示包含了动词“写”，语境“夏天”，以及预期输出“故事”（长文本）。这样的提示能够为 ChatGPT 等 AI 提供清晰的指导。 * **“以表格形式提供2024年奥运会奖牌榜摘要。”** 这个清晰的提示能够确保 AI 提供准确的输出。 本课程将教会您如何清晰地表达您的需求，以从 AI 系统中获得期望的响应。 **祝您学习提示工程 (PE) 顺利！**
In this course, you will learn the three important aspects of prompt engineering - data, context and verb. Prompt Engineering is gaining importance since AI tools/applications require good context setting. Why context setting?Artificial Intelligence (AI) applications are computer systems that do not have memory of previous tasks, they need a context unlike humans who can connect the dots and provide the suitable response. The AI software and tools are performing multiple functionalities in order to simulate a human- like response. If the AI software is not provided with the context and the sample data the response will not be appropriate for the users. For e.g. When you provide a prompt to chat GPT "Please write me a story on summer". This prompt has the verb "write", context "summer" and the sample response "story" so elongated text. So that provides a complete picture to chatGPT.Similarly when you provide the prompt "Give me a summary of medals for Olympics 2024 in table format" This prompt will provide the output accurately.One must know what one wants as response in order to elicit the correct response from AI systems. This course will teach you that information. Good luck on learning Prompt Engineering (PE)!
