Vanderbilt University

OpenAI GPTs: Creating Your Own Custom AI Assistants

深入了解一个主题并学习基础知识。

759 条评论

初级 等级
无需具备相关经验
灵活的计划
7 小时 完成
自行安排学习进度
98%
大多数学生喜欢此课程
深入了解一个主题并学习基础知识。

759 条评论

初级 等级
无需具备相关经验
灵活的计划
7 小时 完成
自行安排学习进度
98%
大多数学生喜欢此课程

要了解的详细信息

可分享的证书

添加到您的领英档案

授课语言:英语(English)

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

此课程作为 的一部分提供
在注册此课程时,您还需要选择一个特定的合作项目。
  • 向行业专家学习新概念
  • 获得对主题或工具的基础理解
  • 通过实践项目培养工作相关技能
  • 获得可共享的职业证书

该课程共有3个模块

In this module, you will learn the core concepts behind building custom GPTs, including how to shape a GPT’s behavior through instructions, add relevant external knowledge using retrieval-augmented generation (RAG), and bring these elements together into a more capable and personalized AI assistant. You will also explore how tools and actions expand what a custom GPT can do, and how frameworks such as CAPITAL, prompt patterns, and persona design can be used to shape its tone, behavior, and overall user experience.

涵盖的内容

7个视频4篇阅读材料2个作业

In this module, you will learn how to make custom GPTs more reliable, useful, and human-centered by testing them systematically and designing better interaction patterns. You will explore how to build simple benchmarks and create meaningful test cases, including expected, ambiguous, and high-risk scenarios, to evaluate GPT performance over time. You will also examine techniques such as direct quotations, output templates, the Flipped Interaction Pattern, menu-based navigation, and feature toggles to structure responses, gather the right context, and guide users more effectively. Throughout the module, the focus is on building GPTs that support human reasoning, surface ambiguity, and direct users toward the right evidence, options, or human support when needed.

涵盖的内容

14个视频4篇阅读材料3个作业

In this module, you will learn how to make custom GPTs safer and more reliable when users ask unclear, ambiguous, or risky questions. You will explore how to define boundaries and ‘escape valves’ so a GPT knows when not to answer directly, how to handle ambiguity, conflicting information, or gaps in knowledge sources and user prompts, and how to guide users more effectively through prompt patterns such as question refinement, alternative approaches, and cognitive verification. By the end of the module, you will understand how to design custom GPTs that remain helpful while reducing the risk of misleading, overconfident, or unsupported responses.

涵盖的内容

10个视频3篇阅读材料1个作业

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

授课教师评分
(251个评价)
Dr. Jules White

顶尖授课教师

Vanderbilt University
51 门课程1,123,041 名学生

提供方

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

自 2018开始学习的学生
''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情,我就可以学习。'

Jennifer J.

自 2020开始学习的学生
''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

Larry W.

自 2021开始学习的学生
''如果我的大学不提供我需要的主题课程,Coursera 便是最好的去处之一。'

Chaitanya A.

''学习不仅仅是在工作中做的更好:它远不止于此。Coursera 让我无限制地学习。'

学生评论

  • 5 stars

    87.23%

  • 4 stars

    10%

  • 3 stars

    1.05%

  • 2 stars

    0.52%

  • 1 star

    1.18%

显示 3/759 个

JH

已于 May 25, 2024审阅

SB

已于 Jul 26, 2025审阅

KD

已于 Oct 22, 2025审阅

¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。