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所在平台: Udemy |
课程主页: https://www.udemy.com/course/prompt-engineering-for-everyone-bootcamp/
课程评论：没有评论
课程名称：人人必备的提示工程训练营 课程概述：提示工程是人工智能时代最需和最具前景的技能之一。本课程将教您如何掌握这一技能。该课程采用实践导向，不依赖特定工具，专为希望充分利用大型语言模型（如ChatGPT、Claude、Gemini等）的专业人士、教育工作者、开发者、分析师和创意人员设计。您将学习如何与AI协作，通过创建结构化、上下文相关的提示，生成准确、有用且安全的输出，而不是将其视为一个黑箱。 课程从基础概念入手，包括提示工程的定义、重要性，以及不同类型提示（如零样本、少样本、思维链、角色基础等）对结果的影响。您将掌握大型语言模型如何生成语言、什么是“token”，以及为何有时会出现幻觉或未能遵循指令。 随后，我们将深入探讨设计有效提示的现实策略。您将学习如何提供适当的上下文、测试和调整提示，甚至使用元提示（让模型帮助您设计更好的提示）。每个概念都通过各个领域的实际示例和引导练习进行强化，包括教育、医疗、法律、市场营销、软件开发和数据科学。 您还将探索高级概念，如提示调优、混合提示和伦理AI使用，包括如何减少偏见、避免有害内容和确保隐私。课程的最后一个模块是关于减少幻觉的，您将学习如何提示模型，以减少虚假或虚构的输出。 不需要编程背景，具有技术倾向的学习者还可以选择模块学习模型架构（如Transformer）和提示优化技术。 学习内容： - 提示工程的核心原则 - 大型语言模型的工作原理及提示结构的重要性 - 提示策略的类型及其使用时机 - 如何迭代、测试和改进提示以提升性能 - 使用元提示构建更好的提示模板 - 减少幻觉并引导模型朝向事实准确性 - 在实际应用中伦理地使用AI - 针对不同媒介（文字、代码、图像）的提示技术 适合人群： - 希望自动化任务、改善工作流程或构建AI集成工具的专业人士 - 设计个性化学习材料或AI辅助内容的教育工作者 - 寻求与AI创造性合作的作家、市场营销人员和设计师 - 寻找可靠、可重复提示的开发者和数据分析师 - 希望更安全、高效、有意识地使用AI的任何人
Prompt engineering is one of the most in-demand and future-proof skills of the AI era - and this course will teach you how to master it.This hands-on, tool-agnostic course is designed for professionals, educators, developers, analysts, and creatives who want to harness the full potential of large language models (LLMs) like ChatGPT, Claude, Gemini, and others. Instead of treating AI like a black box, you'll learn how to collaborate with it by crafting structured, context-aware prompts that generate accurate, useful, and safe outputs.The course starts with foundational concepts - what prompt engineering is, why it matters, and how different types of prompts (zero-shot, few-shot, chain-of-thought, role-based, etc.) impact outcomes. You'll gain a working understanding of how LLMs generate language, what "tokens" are, and why they sometimes hallucinate or fail to follow instructions.From there, we dive into real-world strategies for designing effective prompts. You'll learn how to give the model the right amount of context, test and tune your prompts, and even use meta prompting - prompting the model to help you design better prompts. Each concept is reinforced with practical examples and guided exercises across domains like education, healthcare, legal, marketing, software development, and data science.You'll also explore advanced concepts like prompt tuning, hybrid prompting, and ethical AI use - including how to minimize bias, avoid harmful content, and ensure privacy. The course finishes with a capstone module on hallucination reduction, where you'll learn how to prompt the model in ways that reduce false or fabricated outputs.No programming background is required, though technically-inclined learners will find optional advanced modules on model architecture (e.g., Transformers) and prompt optimization techniques.What You'll Learn:Core principles of prompt engineeringHow LLMs work and why prompt structure mattersTypes of prompting strategies and when to use themHow to iterate, test, and refine your prompts for better performanceUsing meta prompting to build better prompt templatesReducing hallucination and guiding the model toward factual accuracyEthical use of AI in real-world applicationsPrompting for different modalities (text, code, image)Who This Course Is For:Professionals who want to automate tasks, improve workflows, or build AI-integrated toolsEducators designing personalized learning materials or AI-assisted contentWriters, marketers, and designers looking to collaborate with AI creativelyDevelopers and data analysts seeking reliable, repeatable prompts for technical workAnyone who wants to use AI more safely, effectively, and intentionally
