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この入門レベルのマイクロラーニング コースでは、責任ある AI の概要と重要性、および Google が責任ある AI を自社プロダクトにどのように実装しているのかについて説明します。また、Google の AI に関する 7 つの原則についても説明します。
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What's inside
Syllabus
責任ある AI の概要
この入門レベルのマイクロラーニング コースでは、責任ある AI の概要と重要性、および Google が責任ある AI を自社プロダクトにどのように実装しているのかについて説明します。また、Google の AI に関する 7 つの原則についても説明します。
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches the importance of responsible AI, which is crucial for understanding AI's ethical implications
Develops an understanding of Google's 7 principles for AI, providing learners with a framework for ethical AI
Helps learners understand how Google implements responsible AI into its products, providing practical examples
Suitable for beginners, providing a solid foundation in responsible AI
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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 Introduction to Responsible AI - 日本語版 with these
activities:
AI Foundations Refresher
Show steps
Review foundational concepts in AI and programming to ensure a smoother experience in the course.
Browse courses on
Machine Learning
Show steps
-
Revisit basic programming concepts like variables, data types, and control flow.
-
Review fundamental machine learning algorithms like supervised and unsupervised learning.
-
Explore the basics of AI, including its types, applications, and ethical implications.
AI Resources Compilation
Show steps
Gather and organize a collection of valuable AI-related resources for future reference.
Show steps
-
Explore various online sources to identify and collect relevant AI resources.
-
Organize the resources into categories or subtopics for easy access.
-
Share your compilation with other students or the wider AI community.
Google AI Platform Guided Tutorials
Show steps
Supplement course content with hands-on tutorials from Google, providing a practical understanding of the AI Platform.
Browse courses on
Google AI Platform
Show steps
-
Follow guided tutorials on building and deploying AI models using Google AI Platform.
-
Explore specific tutorials relevant to your interests and learning objectives.
-
Experiment with different AI services and features offered by Google Cloud.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Peer Discussion Groups
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Engage with fellow learners to exchange insights, ask questions, and provide feedback.
Browse courses on
Group Discussions
Show steps
-
Join or form peer discussion groups to connect with other students.
-
Participate in discussions, share your perspectives, and ask for assistance.
-
Provide feedback and support to other group members.
AI Project Proposal
Show steps
Apply course concepts by developing a proposal for an AI project that addresses a real-world problem.
Show steps
-
Identify a problem or challenge that can be addressed using AI.
-
Research and explore existing AI solutions for the identified problem.
-
Develop a detailed project proposal outlining the goals, methodology, and expected outcomes.
AI Industry Workshops
Show steps
Attend industry workshops led by experts to gain practical knowledge and insights into real-world AI applications.
Browse courses on
Industry Trends
Show steps
-
Research and identify industry workshops or events focused on AI.
-
Register and attend workshops that align with your interests and learning goals.
-
Actively participate in workshops, ask questions, and network with professionals.
Become an AI Mentor
Show steps
Share your knowledge and support fellow learners by becoming a mentor for AI enthusiasts.
Browse courses on
Mentorship
Show steps
-
Join online or local AI communities and forums.
-
Identify individuals who could benefit from your guidance and support.
-
Provide mentorship and support, sharing your knowledge and experience in AI.
AI Foundations Refresher
Show steps
Review foundational concepts in AI and programming to ensure a smoother experience in the course.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Revisit basic programming concepts like variables, data types, and control flow.
- Review fundamental machine learning algorithms like supervised and unsupervised learning.
- Explore the basics of AI, including its types, applications, and ethical implications.
AI Resources Compilation
Show steps
Gather and organize a collection of valuable AI-related resources for future reference.
Show steps
Show steps
Show steps
- Explore various online sources to identify and collect relevant AI resources.
- Organize the resources into categories or subtopics for easy access.
- Share your compilation with other students or the wider AI community.
Google AI Platform Guided Tutorials
Show steps
Supplement course content with hands-on tutorials from Google, providing a practical understanding of the AI Platform.
Browse courses on
Google AI Platform
Show steps
Show steps
Show steps
- Follow guided tutorials on building and deploying AI models using Google AI Platform.
- Explore specific tutorials relevant to your interests and learning objectives.
- Experiment with different AI services and features offered by Google Cloud.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Peer Discussion Groups
Show steps
Engage with fellow learners to exchange insights, ask questions, and provide feedback.
Browse courses on
Group Discussions
Show steps
Show steps
Show steps
- Join or form peer discussion groups to connect with other students.
- Participate in discussions, share your perspectives, and ask for assistance.
- Provide feedback and support to other group members.
AI Project Proposal
Show steps
Apply course concepts by developing a proposal for an AI project that addresses a real-world problem.
Show steps
Show steps
Show steps
- Identify a problem or challenge that can be addressed using AI.
- Research and explore existing AI solutions for the identified problem.
- Develop a detailed project proposal outlining the goals, methodology, and expected outcomes.
AI Industry Workshops
Show steps
Attend industry workshops led by experts to gain practical knowledge and insights into real-world AI applications.
Browse courses on
Industry Trends
Show steps
Show steps
Show steps
- Research and identify industry workshops or events focused on AI.
- Register and attend workshops that align with your interests and learning goals.
- Actively participate in workshops, ask questions, and network with professionals.
Become an AI Mentor
Show steps
Share your knowledge and support fellow learners by becoming a mentor for AI enthusiasts.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Join online or local AI communities and forums.
- Identify individuals who could benefit from your guidance and support.
- Provide mentorship and support, sharing your knowledge and experience in AI.
Career center
Learners who complete Introduction to Responsible AI - 日本語版 will develop knowledge and skills
that may be useful to these careers:
AI Architect
AI Architect
An AI Architect is a technical expert responsible for designing, implementing, and maintaining end-to-end AI systems. This course is directly relevant to this position as it provides a strong introduction to responsible AI principles and practices, and Google's approach to implementing responsible AI in its products. As responsible AI becomes increasingly crucial across industries, this course will equip you with sought-after knowledge to succeed as an AI Architect.
AI Compliance Officer
AI Compliance Officer
An AI Compliance Officer is responsible for ensuring that an organization's AI systems and practices comply with ethical and regulatory guidelines. This course is extremely relevant to the role, as it provides a comprehensive overview of responsible AI principles and practices, as well as Google's approach to implementing responsible AI. By taking this course, you will gain the essential knowledge to excel in AI Compliance.
AI Policy Advisor
AI Policy Advisor
An AI Policy Advisor advises government, businesses, and other organizations on the ethical and legal implications of AI development and use. This course is highly relevant as it helps you understand the principles of responsible AI, the impact of AI on society, and the regulatory landscape around AI. Taking this course will lay a solid foundation for your career as an AI Policy Advisor.
AI Auditor
AI Auditor
An AI Auditor is an independent expert who assesses the ethical and social impact of AI systems. This course is useful for AI Auditors, as it provides a solid understanding of responsible AI principles and practices, as well as the regulatory landscape around AI. Taking this course will help you develop the skills needed to evaluate AI systems for potential risks and benefits.
AI Risk Manager
AI Risk Manager
An AI Risk Manager identifies and manages the risks associated with AI systems. This course is valuable for AI Risk Managers, as it provides a clear understanding of the potential risks of AI and how to mitigate them through responsible design and implementation. The course will also provide you with a framework for assessing AI risks and developing risk mitigation strategies.
Data Scientist
Data Scientist
A Data Scientist develops and implements AI models and algorithms. This course is highly relevant to Data Scientists, as it will help you understand the principles of responsible AI and how to apply them in your work. The course will help you identify and mitigate potential biases in data and models, and ensure that AI systems are developed in a fair and equitable manner.
Product Manager
Product Manager
A Product Manager is responsible for the development and management of a product. This course may be useful for Product Managers interested in launching or managing AI-powered products, as it provides insights into the ethical and societal implications of AI. By taking this course, you will gain the knowledge and skills to develop and manage AI-powered products that are responsible and beneficial to society.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course may be useful for Software Engineers interested in developing AI systems, as it provides a foundation in responsible AI principles and practices. By taking this course, you will gain the knowledge and skills to design, develop, and test AI systems that are fair, equitable, and responsible.
Consultant
Consultant
A Consultant provides advice and guidance to organizations on a wide range of issues. This course may be useful for Consultants interested in advising clients on AI-related issues, as it provides a foundation in responsible AI principles and practices. By taking this course, you will gain the knowledge and skills to advise clients on the ethical and societal implications of AI and help them develop AI strategies that are responsible and beneficial.
Business Analyst
Business Analyst
A Business Analyst identifies and analyzes business needs and develops solutions to meet those needs. This course may be useful for Business Analysts interested in working with AI systems, as it provides a foundation in responsible AI principles and practices. By taking this course, you will gain the knowledge and skills to analyze the impact of AI on businesses and develop solutions that are responsible and beneficial.
Researcher
Researcher
A Researcher conducts research and develops new knowledge in a particular field. This course may be useful for Researchers interested in studying the ethical and societal implications of AI, as it provides a foundation in responsible AI principles and practices. By taking this course, you will gain the knowledge and skills to conduct research on AI and develop solutions to the challenges posed by AI.
Policy Analyst
Policy Analyst
A Policy Analyst develops and analyzes public policy. This course may be useful for Policy Analysts interested in developing or analyzing AI-related policies, as it provides a foundation in responsible AI principles and practices. By taking this course, you will gain the knowledge and skills to analyze the impact of AI on society and develop policies that are responsible and beneficial.
Journalist
Journalist
A Journalist reports on current events and issues. This course may be useful for Journalists interested in covering AI-related topics, as it provides a foundation in responsible AI principles and practices. By taking this course, you will gain the knowledge and skills to report on AI in an informed and responsible manner.
Educator
Educator
An Educator teaches students at all levels. This course may be useful for Educators interested in teaching about AI, as it provides a foundation in responsible AI principles and practices. By taking this course, you will gain the knowledge and skills to teach AI in a responsible and engaging manner.
Student
Student
A Student is enrolled in an educational program. This course is highly relevant for students interested in pursuing a career in AI, as it provides a solid foundation in responsible AI principles and practices. Taking this course will equip you with the knowledge and skills to develop and implement AI systems that are ethical, fair, and beneficial to society.
For more career information including salaries, visit:
OpenCourser.com/course/2uu53e/introduction
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Responsible AI - 日本語版.
この本は、AI の倫理的影響、バイアスの潜在的な問題、および社会正義に対する影響を調査します。責任ある AI の開発において倫理的な考慮事項を理解するのに役立ちます。
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この本は、AI の歴史、現在、未来を探求します。責任ある AI の開発において、AI の可能性と限界を理解するのに役立ちます。
この本では、責任ある AI の包括的なフレームワークが提供されており、AI システムの倫理的および社会的影響に対する包括的な理解を得ることができます。
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この本は、AI が人間の知性を超える可能性とその影響を探求します。責任ある AI の開発における潜在的なリスクと機会を検討するのに役立ちます。
この本は、Python を使用したディープラーニングの包括的なガイドです。責任ある AI にディープラーニングを適用するために役立ちます。
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この本は、機械学習の入門書であり、基礎、手法、および応用について説明します。責任ある AI の開発において機械学習の役割を理解するのに役立ちます。
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この本は、AI の進歩が人類の進化と文明に与える影響を調査します。責任ある AI の開発における哲学的かつ倫理的な考慮事項を検討するのに役立ちます。
この本は、技術的進歩の指数関数的な性質と、それが私たちの社会と文明に与える影響を探求します。責任ある AI の開発における長期的な視野を形成するのに役立ちます。
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ディープラーニングの理論と実践に関する包括的なガイドとして知られるこの本は、責任ある AI システムの開発に使用される技術的アプローチに対する理解を深めるのに役立ちます。
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アルゴリズムの社会における役割と影響を批判的に考察するこの本は、責任ある AI 実装における透明性、説明可能性、説明責任の重要性についての考察を促します。
AI システムが社会正義に与える影響を調査するこの本は、責任ある AI 実装における倫理的考慮事項と社会への影響に対する認識を高めます。
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AI の将来に関する洞察と考察を提供するこの本は、責任ある AI の実施が人間の未来を形作る上で果たす重要な役割を検討するきっかけになります。
For more information about how these books relate to this course, visit:
OpenCourser.com/course/2uu53e/introduction
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Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
日本語
Transcript
Français
Good to know
Teaches the importance of responsible AI, which is crucial for understanding AI's ethical implications
Develops an understanding of Google's 7 principles for AI, providing learners with a framework for ethical AI
Helps learners understand how Google implements responsible AI into its products, providing practical examples
Suitable for beginners, providing a solid foundation in responsible AI
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