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Google Cloud Training
This course equips learners with the essential knowledge and practical tools to develop and implement artificial intelligence (AI) responsibly. Through an exploration of ethical considerations, best practices, and governance procedures, participants will gain an understanding of how to navigate the complex landscape of AI while upholding ethical standards and minimizing potential risks.
Register for this course and see more details by visiting:
OpenCourser.com/course/j4q5sf/responsible
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What's inside
Syllabus
What is Responsible AI?
This module introduces the concept of responsible AI and covers why there is a need for a robust responsible AI review process, as well as Google's 7 AI principles.
Read more
Syllabus
What is Responsible AI?
This module introduces the concept of responsible AI and covers why there is a need for a robust responsible AI review process, as well as Google's 7 AI principles.
Read more
Best Practices and Guidelines for Responsible AI
This module covers ethical issues that can arise with generative AI solutions and how to address them. It also explains the aim of each of Google's AI principles and key takeaways from Google's process of operationalizing AI principles.
Responsible AI Governance and Review
This module describes common misconceptions about responsible AI governance, how to ask good questions to spot potential ethical issues with an AI solution, and the review bodies within Google's AI governance process.
Next Steps
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines ethical considerations, standards, and governance procedures for responsible AI, fostering ethical decision-making
Led by Google Cloud Training, known for industry-leading AI expertise
Provides practical tools and knowledge for developing and implementing AI responsibly
May require prior knowledge or experience in AI for full comprehension
Emphasizes Google's AI principles and governance process, which may not be universally applicable
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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 Responsible AI for Digital Leaders with Google Cloud with these
activities:
Explore AI tools and frameworks
Show steps
Build a solid foundation in AI by familiarizing yourself with popular tools and frameworks.
Browse courses on
AI Tools
Show steps
-
Research and identify popular AI tools and frameworks used in various industries
-
Follow tutorials and documentation to understand their capabilities and limitations
-
Experiment with different tools and frameworks to gain hands-on experience
Curate a collection of AI resources
Show steps
Organize and gather valuable AI resources to support your learning and development.
Show steps
-
Identify and collect reputable sources of information on AI, such as articles, books, and online courses
-
Organize the resources into a central location or platform for easy access
-
Share your curated collection with peers or fellow learners
Engage in AI ethics discussions
Show steps
Exchange perspectives on ethical implications of AI and develop a nuanced understanding of responsible AI.
Browse courses on
AI Ethics
Show steps
-
Join online forums or discussion groups dedicated to AI ethics
-
Participate in debates and share insights on real-world AI ethical dilemmas
-
Collaborate with peers to develop a code of ethics for AI development
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore best practices for AI governance
Show steps
Gain in-depth knowledge of AI governance frameworks and best practices to enhance your understanding of responsible AI.
Browse courses on
AI Governance
Show steps
-
Identify reputable sources for AI governance guidelines
-
Review tutorials and case studies on successful AI governance implementations
-
Discuss AI governance strategies with peers or industry experts
Practice AI implementation scenarios
Show steps
Reinforce your understanding of AI implementation principles by completing practical exercises.
Browse courses on
AI Implementation
Show steps
-
Set up a coding environment for AI development
-
Select a dataset and familiarize yourself with its structure
-
Apply AI algorithms to the dataset to solve a specific problem
Practice implementing AI principles
Show steps
Enhance your understanding of AI principles and their practical application through hands-on exercises.
Browse courses on
AI Principles
Show steps
-
Identify real-world scenarios where AI principles can be applied
-
Develop a plan for implementing the principles in these scenarios
-
Build and deploy AI solutions that incorporate these principles
Develop an AI case study analysis
Show steps
Demonstrate your understanding of responsible AI by analyzing a real-world case study.
Show steps
-
Choose a case study that showcases the implementation of AI in a specific industry or domain
-
Thoroughly analyze the case study, paying attention to the ethical considerations and responsible AI practices employed
-
Present your analysis in a written report or multimedia presentation
Contribute to open-source AI projects
Show steps
Gain practical experience in responsible AI development by contributing to open-source projects.
Browse courses on
AI Development
Show steps
-
Identify open-source AI projects aligned with your interests and skills
-
Review the project's codebase and documentation to understand its goals and implementation
-
Make contributions to the project, such as bug fixes, feature enhancements, or documentation improvements
Explore AI tools and frameworks
Show steps
Build a solid foundation in AI by familiarizing yourself with popular tools and frameworks.
Browse courses on
AI Tools
Show steps
Show steps
Show steps
- Research and identify popular AI tools and frameworks used in various industries
- Follow tutorials and documentation to understand their capabilities and limitations
- Experiment with different tools and frameworks to gain hands-on experience
Curate a collection of AI resources
Show steps
Organize and gather valuable AI resources to support your learning and development.
Show steps
Show steps
Show steps
- Identify and collect reputable sources of information on AI, such as articles, books, and online courses
- Organize the resources into a central location or platform for easy access
- Share your curated collection with peers or fellow learners
Engage in AI ethics discussions
Show steps
Exchange perspectives on ethical implications of AI and develop a nuanced understanding of responsible AI.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Join online forums or discussion groups dedicated to AI ethics
- Participate in debates and share insights on real-world AI ethical dilemmas
- Collaborate with peers to develop a code of ethics for AI development
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore best practices for AI governance
Show steps
Gain in-depth knowledge of AI governance frameworks and best practices to enhance your understanding of responsible AI.
Browse courses on
AI Governance
Show steps
Show steps
Show steps
- Identify reputable sources for AI governance guidelines
- Review tutorials and case studies on successful AI governance implementations
- Discuss AI governance strategies with peers or industry experts
Practice AI implementation scenarios
Show steps
Reinforce your understanding of AI implementation principles by completing practical exercises.
Browse courses on
AI Implementation
Show steps
Show steps
Show steps
- Set up a coding environment for AI development
- Select a dataset and familiarize yourself with its structure
- Apply AI algorithms to the dataset to solve a specific problem
Practice implementing AI principles
Show steps
Enhance your understanding of AI principles and their practical application through hands-on exercises.
Browse courses on
AI Principles
Show steps
Show steps
Show steps
- Identify real-world scenarios where AI principles can be applied
- Develop a plan for implementing the principles in these scenarios
- Build and deploy AI solutions that incorporate these principles
Develop an AI case study analysis
Show steps
Demonstrate your understanding of responsible AI by analyzing a real-world case study.
Show steps
Show steps
Show steps
- Choose a case study that showcases the implementation of AI in a specific industry or domain
- Thoroughly analyze the case study, paying attention to the ethical considerations and responsible AI practices employed
- Present your analysis in a written report or multimedia presentation
Contribute to open-source AI projects
Show steps
Gain practical experience in responsible AI development by contributing to open-source projects.
Browse courses on
AI Development
Show steps
Show steps
Show steps
- Identify open-source AI projects aligned with your interests and skills
- Review the project's codebase and documentation to understand its goals and implementation
- Make contributions to the project, such as bug fixes, feature enhancements, or documentation improvements
Career center
Learners who complete Responsible AI for Digital Leaders with Google Cloud will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/j4q5sf/responsible
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Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Session
August 26, 2024
- September 30, 2024
Language
English
Good to know
Examines ethical considerations, standards, and governance procedures for responsible AI, fostering ethical decision-making
Led by Google Cloud Training, known for industry-leading AI expertise
Provides practical tools and knowledge for developing and implementing AI responsibly
May require prior knowledge or experience in AI for full comprehension
Emphasizes Google's AI principles and governance process, which may not be universally applicable
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