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Responsible AI for Digital Leaders with Google Cloud

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.

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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.
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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

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
Build a solid foundation in AI by familiarizing yourself with popular tools and frameworks.
Browse courses on AI Tools
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  • 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
Organize and gather valuable AI resources to support your learning and development.
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  • 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
Exchange perspectives on ethical implications of AI and develop a nuanced understanding of responsible AI.
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  • 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
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Explore best practices for AI governance
Gain in-depth knowledge of AI governance frameworks and best practices to enhance your understanding of responsible AI.
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  • 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
Reinforce your understanding of AI implementation principles by completing practical exercises.
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  • 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
Enhance your understanding of AI principles and their practical application through hands-on exercises.
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  • 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
Demonstrate your understanding of responsible AI by analyzing a real-world case study.
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  • 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
Gain practical experience in responsible AI development by contributing to open-source projects.
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  • 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:

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Course image
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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