We may earn an affiliate commission when you visit our partners.
Google Cloud Training
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。
Register for this course and see more details by visiting:
OpenCourser.com/course/imcxkh/responsible
Three deals to help you save
We found three deals and offers that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until December 12
Annual Subscription Savings
Unlock programs from Google, Microsoft, and IBM and join 77% of learners who reported positive career outcomes.
Only $239!
Valid for a limited time only
Future-proof your career
Access O'Reilly books, live events, courses, and more. Save with an annual subscription.
Take
15%
off
What's inside
Syllabus
課程簡介
本單元介紹課程架構和目標。
AI 可解釋性和透明度
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。
Read more
Syllabus
課程簡介
本單元介紹課程架構和目標。
AI 可解釋性和透明度
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。
Read more
課程摘要
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。
課程資源
連結至所有單元的學員用 PDF
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
適合想要學習 AI 可解釋性和透明度基礎知識的學習者。
有助於開發人員和工程師讓資料和 AI 模型更易於理解。
授課講師為 Google Cloud Training，在相關領域具有專業知識。
Save this course
Save Responsible AI for Developers: Interpretability & Transparency - 繁體中文 to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Responsible AI for Developers: Interpretability & Transparency - 繁體中文 with these
activities:
Review Statistics Concepts
Show steps
Refreshing statistics knowledge helps students better understand the statistical models and data analysis techniques used in AI.
Browse courses on
Statistics
Show steps
-
Review basic statistical concepts, such as mean, median, and standard deviation
-
Practice applying statistical methods to real-world AI datasets
Connect with AI Professionals
Show steps
Connecting with professionals in the AI field provides valuable insights, career advice, and potential mentorship opportunities.
Browse courses on
Career Development
Show steps
-
Attend industry events or conferences
-
Reach out to AI professionals on LinkedIn
-
Seek guidance from professors or teaching assistants
Explore Interactive AI Demonstrations
Show steps
Interactive demonstrations provide visual and practical insights into AI concepts, making them more accessible and engaging.
Browse courses on
AI Applications
Show steps
-
Search for online AI demonstrations or tutorials
-
Choose a demonstration that relates to the course topics
-
Follow the instructions and explore the interactive elements
Four other activities
Expand to see all activities and additional details
Show all seven activities
Summarize AI Techniques
Show steps
Creating summaries of AI techniques covered in this course helps improve memorization and understanding of the topic.
Browse courses on
AI Techniques
Show steps
-
Review notes and materials from the course
-
Summarize each technique in a few sentences, highlighting its purpose and key features
-
Create a document or presentation with your summaries
Solve AI Algorithm Problems
Show steps
Solving AI algorithm problems enhances critical thinking, problem-solving skills, and deepens understanding of AI techniques.
Browse courses on
AI Algorithms
Show steps
-
Find online platforms or textbooks with AI algorithm problems
-
Choose problems that relate to the course topics
-
Implement the algorithms and test their performance
Practice Explaining AI Terms
Show steps
Explaining AI concepts to peers reinforces understanding and strengthens communication skills.
Browse courses on
AI Transparency
Show steps
-
Form a study group with other students
-
Choose an AI term or concept to present
-
Prepare a brief presentation explaining the term
-
Take turns presenting and explaining to each other
Design an AI Transparency Framework
Show steps
Creating an AI transparency framework helps students delve into the ethical implications of AI and develop critical thinking skills.
Browse courses on
AI Transparency
Show steps
-
Research ethical guidelines and best practices for AI transparency
-
Identify key stakeholders and their concerns
-
Design a framework that outlines transparency measures, data collection, and communication strategies
-
Present your framework to the class for feedback
Review Statistics Concepts
Show steps
Refreshing statistics knowledge helps students better understand the statistical models and data analysis techniques used in AI.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Review basic statistical concepts, such as mean, median, and standard deviation
- Practice applying statistical methods to real-world AI datasets
Connect with AI Professionals
Show steps
Connecting with professionals in the AI field provides valuable insights, career advice, and potential mentorship opportunities.
Browse courses on
Career Development
Show steps
Show steps
Show steps
- Attend industry events or conferences
- Reach out to AI professionals on LinkedIn
- Seek guidance from professors or teaching assistants
Explore Interactive AI Demonstrations
Show steps
Interactive demonstrations provide visual and practical insights into AI concepts, making them more accessible and engaging.
Browse courses on
AI Applications
Show steps
Show steps
Show steps
- Search for online AI demonstrations or tutorials
- Choose a demonstration that relates to the course topics
- Follow the instructions and explore the interactive elements
Four other activities
Expand to see all activities and additional details
Show all seven activities
Summarize AI Techniques
Show steps
Creating summaries of AI techniques covered in this course helps improve memorization and understanding of the topic.
Browse courses on
AI Techniques
Show steps
Show steps
Show steps
- Review notes and materials from the course
- Summarize each technique in a few sentences, highlighting its purpose and key features
- Create a document or presentation with your summaries
Solve AI Algorithm Problems
Show steps
Solving AI algorithm problems enhances critical thinking, problem-solving skills, and deepens understanding of AI techniques.
Browse courses on
AI Algorithms
Show steps
Show steps
Show steps
- Find online platforms or textbooks with AI algorithm problems
- Choose problems that relate to the course topics
- Implement the algorithms and test their performance
Practice Explaining AI Terms
Show steps
Explaining AI concepts to peers reinforces understanding and strengthens communication skills.
Browse courses on
AI Transparency
Show steps
Show steps
Show steps
- Form a study group with other students
- Choose an AI term or concept to present
- Prepare a brief presentation explaining the term
- Take turns presenting and explaining to each other
Design an AI Transparency Framework
Show steps
Creating an AI transparency framework helps students delve into the ethical implications of AI and develop critical thinking skills.
Browse courses on
AI Transparency
Show steps
Show steps
Show steps
- Research ethical guidelines and best practices for AI transparency
- Identify key stakeholders and their concerns
- Design a framework that outlines transparency measures, data collection, and communication strategies
- Present your framework to the class for feedback
Career center
Learners who complete Responsible AI for Developers: Interpretability & Transparency - 繁體中文 will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/imcxkh/responsible
Reading list
We haven't picked any books for this reading list yet.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/imcxkh/responsible
Share
Similar courses
Here are nine courses similar to
Responsible AI for Developers: Interpretability & Transparency - 繁體中文.
Responsible AI for Developers: Interpretability & Transparency - 简体中文
OpenCourser.com/course/s3ro71/responsible
Responsible AI for Developers: Interpretability &...
Most relevant
Gemini for Application Developers - 繁體中文
OpenCourser.com/course/xp284i/gemini
Gemini for Application Developers - 繁體中文
Most relevant
線性代數 (Linear Algebra)
OpenCourser.com/course/zw2sjg/Xian
線性代數 (Linear Algebra)
Most relevant
Introduction to AI and Machine Learning on GC - 繁體中文
OpenCourser.com/course/twj1xa/introduction
Introduction to AI and Machine Learning on GC - 繁體中文
Most relevant
Generative AI第一部 - 從LangChain接入ChatGPT到製作股票分析AI團隊
OpenCourser.com/course/js2ssc/generative
Generative AI第一部 - 從LangChain接入ChatGPT到製作股票分析AI團隊
Most relevant
Gemini for Cloud Architects - 繁體中文
OpenCourser.com/course/e7bd0k/gemini
Gemini for Cloud Architects - 繁體中文
Most relevant
CAD/BIM技術與應用專項課程（CAD/BIM Specialization)
OpenCourser.com/course/196vvt/cad
CAD/BIM技術與應用專項課程（CAD/BIM Specialization)
Most relevant
Gemini for DevOps Engineers - 繁體中文
OpenCourser.com/course/4hopab/gemini
Gemini for DevOps Engineers - 繁體中文
Most relevant
Responsible AI for Developers: Fairness & Bias - 繁體中文
OpenCourser.com/course/2yphp6/responsible
Responsible AI for Developers: Fairness & Bias - 繁體中文
Most relevant
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Session
August 19, 2024
- September 23, 2024
Language
zh-TW
Good to know
適合想要學習 AI 可解釋性和透明度基礎知識的學習者。
有助於開發人員和工程師讓資料和 AI 模型更易於理解。
授課講師為 Google Cloud Training，在相關領域具有專業知識。
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser