本課程旨在說明 AI 的可解釋性和透明度概念、探討 AI 透明度對開發人員和工程師的重要性。課程中也會介紹實務方法和工具，有助於讓資料和 AI 模型透明且可解釋。
Responsible AI for Developers: Interpretability & Transparency - 繁體中文
Responsible AI for Developers: Interpretability & Transparency - 繁體中文
Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
定義 AI 的可解釋性和透明度
說明 AI 可解釋性和透明度的重要性
瞭解各項實用工具與技術，打造兼顧可解釋性和透明度的 AI
Details to know
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Recently updated!
July 2024
Assessments
1 assignment
Taught in Chinese (Traditional)
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There are 4 modules in this course
本單元介紹課程架構和目標。
What's included
1 video
本單元著重介紹 AI 的可解釋性和透明度，並提供多種技術與工具，有助於讓資料和 AI 模型透明且可解釋。
What's included
9 videos1 assignment1 app item
本單元介紹最重要的概念、工具和技術，概略說明整個課程內容。
What's included
1 video1 reading
連結至所有單元的學員用 PDF
What's included
3 readings
Instructor
Offered by
Recommended if you're interested in Cloud Computing
Board Infinity
Duke University
Whizlabs
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.