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Ria Cheruvu

Learn how to approach and apply the ethics of artificial intelligence with Udacity. Develop ethical AI literacy and apply key concepts and principles at the business level.

Prerequisite details

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Learn how to approach and apply the ethics of artificial intelligence with Udacity. Develop ethical AI literacy and apply key concepts and principles at the business level.

Prerequisite details

To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:

  • AI fluency
  • Python data analysis libraries
  • Machine learning model implementation
  • Pandas
  • Data visualization
  • matplotlib

You will also need to be able to communicate fluently and professionally in written and spoken English.

What's inside

Syllabus

Learn the fundamentals of AI Ethics, including the definitions, history, context, and stakeholders involved with this domain!
Learn how to articulate and apply ethical AI for organizations and businesses, including how bias applies to organizations, ethical AI principles and programs, and guardrails!
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Learn how to identify the different types of AI biases and harms, and apply harm quantification metrics for evaluating fairness!
Learn how to mitigate bias, including comparisons between strategies and metrics, and applying techniques toward enhancing fairness!
Learn how to articulate context around AI regulations, data governance, and auditing! Along the way, you will also learn how to apply techniques for transparency and explainability.
Test your skills for identifying the ethical impact of a use case! You'll perform quantitative analyses, mitigate bias, and create a model card to document the ethical impact and your findings!

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores AI ethics, including definitions, history, and context
Teaches how to apply ethical AI for organizations and businesses
Develops skills in identifying and mitigating AI biases and harms
Examines AI regulations, data governance, and auditing
Taught by Ria Cheruvu, an experienced instructor in AI ethics
Requires prior knowledge in AI, Python data analysis libraries, machine learning model implementation, Pandas, data visualization, and matplotlib

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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 Ethical AI with these activities:
Read 'Ethics of Artificial Intelligence' by S. Wallach and W. Allen
Gain insights into foundational ethical considerations in the field of AI by reading this comprehensive text.
Show steps
  • Read and take notes on the key chapters
  • Identify and summarize the main ethical principles and arguments presented
  • Reflect on the implications of these principles for your own understanding and practice of AI
Review Python programming basics
Review the basics of Python programming language to enhance your understanding of the course concepts and coding practices.
Browse courses on Python
Show steps
  • Read documentation and tutorials on Python basics
  • Practice coding simple Python programs to reinforce concepts
Brush up on Python Data Analysis Libraries
Familiarize yourself with the Python data analysis libraries to enhance your ability to work with data in this course.
Browse courses on Python
Show steps
  • Review documentation for Pandas and matplotlib
  • Complete a tutorial or online course on data analysis using Python
  • Practice working with sample datasets
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Participate in online discussion forums
Engage in discussions with peers to exchange ideas, clarify concepts, and deepen your understanding of ethical AI.
Show steps
  • Join relevant online discussion forums
  • Participate in discussions by asking questions and sharing insights
  • Read and respond to the contributions of others
Follow tutorials on ethical AI principles and applications
Enhance your understanding of ethical AI by following guided tutorials and exploring real-world applications of ethical principles.
Show steps
  • Identify reputable sources for ethical AI tutorials
  • Select tutorials aligned with your interests and goals
  • Complete tutorials and take notes on key concepts
  • Apply techniques from tutorials to evaluate ethical AI practices
Explore Hands-on AI Ethics Case Studies
Enhance your understanding of AI ethics through real-world case studies, solidifying your ability to apply ethical principles.
Show steps
  • Identify and select relevant case studies
  • Analyze the ethical implications and decision-making processes involved
  • Summarize your findings and share your insights
Attend an AI Ethics Workshop
Engage with experts and practitioners to deepen your understanding of AI ethics and best practices.
Show steps
  • Research and identify relevant AI ethics workshops
  • Register and attend the workshop
  • Actively participate in discussions and activities
Participate in AI Ethics Hackathons or Challenges
Apply your understanding of AI ethics in a competitive environment, fostering innovation and problem-solving skills.
Show steps
  • Research and identify relevant AI ethics hackathons or challenges
  • Form a team or collaborate with others
  • Develop and submit your solution
  • Present your solution and receive feedback
Case study analysis on ethical AI implementation
Apply your knowledge of ethical AI principles to a practical scenario by conducting a comprehensive case study analysis.
Browse courses on Case Study Analysis
Show steps
  • Research and select a relevant case study
  • Identify ethical considerations and potential biases in the case
  • Analyze the ethical implications of the AI system's implementation
  • Develop recommendations for improving ethical outcomes
  • Present your findings and recommendations in a written report
Develop a Model Card for an AI System
Gain practical experience in documenting the ethical impact of an AI system, fostering transparency and accountability.
Show steps
  • Choose an existing or hypothetical AI system
  • Identify potential biases and harms associated with the system
  • Quantify the system's performance and fairness metrics
  • Create a model card that clearly communicates the ethical implications and findings
Contribute to Open-Source AI Ethics Projects
Gain practical experience in applying AI ethics principles by contributing to open-source projects that address ethical challenges.
Show steps
  • Identify open-source projects focused on AI ethics
  • Read the project documentation and codebase
  • Identify areas where you can contribute
  • Propose and submit your contributions
Draft an Ethical AI White Paper
Develop a comprehensive understanding of AI ethics by synthesizing your knowledge and insights into a white paper.
Show steps
  • Research and gather information on AI ethics principles and frameworks
  • Identify specific ethical issues or challenges in the field of AI
  • Propose and discuss potential solutions and recommendations
  • Write and revise the white paper

Career center

Learners who complete Ethical AI will develop knowledge and skills that may be useful to these careers:
AI Engineer
AI Engineers design, develop, and maintain AI systems. They need to have a strong understanding of AI ethics to ensure that the systems they create are safe and reliable. This course helps build a foundation in AI ethics, making it a valuable resource for AI Engineers who want to advance their careers.
AI Researcher
AI Researchers develop new AI technologies and applications. They need to have a strong understanding of AI ethics to ensure that the technologies they create are safe and beneficial to society. This course provides a strong foundation in AI ethics, making it a valuable resource for AI Researchers who want to advance their careers.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They need to have a strong understanding of AI ethics to ensure that the models they create are fair and unbiased. This course can help Machine Learning Engineers build the ethical AI skills they need to succeed in their roles.
Data Scientist
Data Scientists use statistics, mathematics, and programming to analyze data. They then use this information to help organizations make better decisions. This course provides a strong foundation in AI ethics, fairness, and bias mitigation, making it a valuable resource for Data Scientists who want to work on AI projects responsibly.
Product Manager
Product Managers are responsible for the development and launch of new products. They need to have a strong understanding of AI ethics to ensure that the products they create are safe and beneficial to society. This course may be helpful for Product Managers who want to learn more about AI ethics and how to apply it to their work.
Risk Manager
Risk Managers help organizations identify and mitigate risks. They need to have a strong understanding of AI ethics to ensure that the risks associated with AI are properly managed. This course may be helpful for Risk Managers who want to learn more about AI ethics and how to apply it to their work.
Auditor
Auditors examine the financial statements of organizations to ensure that they are accurate and complete. They need to have a strong understanding of AI ethics to ensure that the audits they perform are fair and impartial. This course may be helpful for Auditors who want to learn more about AI ethics and how to apply it to their work.
Data Governance Specialist
Data Governance Specialists are responsible for ensuring that data is used in a responsible and ethical manner. They need to have a strong understanding of AI ethics to ensure that data is used to benefit society, not harm it. This course may be helpful for Data Governance Specialists who want to learn more about AI ethics and how to apply it to their work.
Compliance Officer
Compliance Officers ensure that organizations comply with laws and regulations. They need to have a strong understanding of AI ethics to ensure that the organization is using AI in a responsible and ethical manner. This course may be helpful for Compliance Officers who want to learn more about AI ethics and how to apply it to their work.
Lawyer
Lawyers advise clients on legal matters and represent them in court. They need to have a strong understanding of AI ethics to ensure that the advice they give is ethical and responsible. This course may be helpful for Lawyers who want to learn more about AI ethics and how to apply it to their work.
Ethnologist
Ethnologists study the cultures of different societies. They can work with AI systems to learn more about how people interact with them, and what cultural effects the systems might have. This course provides a strong foundation in AI ethics, including how AI systems can be biased, and what strategies can be used to mitigate bias. This course may be helpful for Ethnologists who want to work with AI systems in a responsible way.
AI Policy Analyst
AI Policy Analysts develop and implement policies that govern the use of AI. They need to have a strong understanding of AI ethics to ensure that policies are fair and equitable. This course may be helpful for AI Policy Analysts who want to learn more about AI ethics and how to apply it to their work.
Business Analyst
Business Analysts help organizations improve their efficiency and effectiveness. They need to have a strong understanding of AI ethics to ensure that the recommendations they make are ethical and responsible. This course may be helpful for Business Analysts who want to learn more about AI ethics and how to apply it to their work.
Software Engineer
Software Engineers design, develop, and maintain software applications. They need to have a strong understanding of AI ethics to ensure that the applications they create are safe and reliable. This course may be helpful for Software Engineers who want to learn more about AI ethics and how to apply it to their work.
Data Analyst
Data Analysts use data to identify trends and patterns. They then use this information to help organizations make better decisions. This course may be helpful for Data Analysts who want to learn more about AI ethics and how to apply it to their work.

Reading list

We've selected 11 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 Ethical AI.
Provides a comprehensive overview of the ethical issues surrounding artificial intelligence, including topics such as privacy, fairness, and accountability.
Provides a comprehensive overview of the field of deep learning, including a discussion of the ethical issues surrounding AI.
Provides a comprehensive overview of the field of machine learning, including a discussion of the ethical issues surrounding AI.
Provides a comprehensive overview of the field of machine learning, including a discussion of the ethical issues surrounding AI.
Provides a comprehensive overview of the field of machine learning, including a discussion of the ethical issues surrounding AI.
Provides a comprehensive overview of the field of machine learning, including a discussion of the ethical issues surrounding AI.

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