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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you use the What-if Tool to identify potential biases in a model trained on mortgage loan applications.
Register for this course and see more details by visiting:
OpenCourser.com/course/xh8qjj/identifying
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What's inside
Syllabus
Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches how to identify biases in AI models, which is key for fairness and accountability in AI systems
Hands-on lab provides practical experience with real-world data, enhancing understanding and application of concepts
Conducted by Google Cloud Training, known for expertise and industry-leading practices in AI
Save this course
Save Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool to your list so you can find it easily later:
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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 Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool with these
activities:
Read 'Fairness in Machine Learning' by Solon Barocas and Andrew Selbst
Show steps
This book provides a comprehensive overview of the ethical and social implications of machine learning, including bias and fairness. Reading it will enhance your understanding of the course material and prepare you for real-world applications.
View
Fairness and Machine Learning
on Amazon
Show steps
Review AI Platform Console Fundamentals
Show steps
Review the basics of the AI Platform Console to strengthen your foundation for this course's exercises.
Browse courses on
AI Platform
Show steps
-
Visit the AI Platform Console documentation.
-
Review the console's navigation and layout.
-
Explore the different sections of the console, such as Models, Datasets, and Jobs.
Participate in online discussion forums
Show steps
Engage in discussions with other learners to reinforce your understanding of the course material and gain different perspectives.
Show steps
-
Identify relevant discussion forums for the course.
-
Read through existing discussions and ask clarifying questions.
-
Share your insights and participate in discussions.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice using the What-if Tool
Show steps
Complete the What-if Tool guided tutorials to gain hands-on experience with the tool's capabilities.
Show steps
-
Follow the Google Cloud tutorial on using the What-if Tool.
-
Work through the examples provided in the tutorial.
-
Experiment with different scenarios using the What-if Tool.
Attend a workshop on AI ethics and bias mitigation
Show steps
Attend a workshop or seminar that focuses on the ethical implications of AI and techniques for mitigating bias. This will provide you with practical insights and best practices.
Show steps
Present your findings from the What-if Tool analysis
Show steps
Create a presentation or report that summarizes your findings from the What-if Tool analysis. This will help you solidify your understanding of the tool and its application.
Show steps
-
Identify the key findings from your What-if Tool analysis.
-
Organize your findings into a logical and coherent presentation.
-
Create visuals and examples to illustrate your findings.
-
Practice presenting your findings clearly and concisely.
Volunteer for a non-profit organization focused on AI ethics
Show steps
Apply your knowledge and skills by volunteering for an organization that promotes responsible AI development and addresses issues of bias and fairness.
Show steps
Create a blog post or article summarizing your learnings
Show steps
Write a blog post or article that summarizes the key concepts and insights you have gained from the course. This will help you solidify your understanding and communicate your knowledge to others.
Show steps
-
Identify the main takeaways from the course.
-
Organize your thoughts into a logical and coherent outline.
-
Write a draft of your blog post or article.
-
Revise and edit your writing for clarity and accuracy.
Read 'Fairness in Machine Learning' by Solon Barocas and Andrew Selbst
Show steps
This book provides a comprehensive overview of the ethical and social implications of machine learning, including bias and fairness. Reading it will enhance your understanding of the course material and prepare you for real-world applications.
View
Fairness and Machine Learning
on Amazon
Show steps
Show steps
Show steps
Review AI Platform Console Fundamentals
Show steps
Review the basics of the AI Platform Console to strengthen your foundation for this course's exercises.
Browse courses on
AI Platform
Show steps
Show steps
Show steps
- Visit the AI Platform Console documentation.
- Review the console's navigation and layout.
- Explore the different sections of the console, such as Models, Datasets, and Jobs.
Participate in online discussion forums
Show steps
Engage in discussions with other learners to reinforce your understanding of the course material and gain different perspectives.
Show steps
Show steps
Show steps
- Identify relevant discussion forums for the course.
- Read through existing discussions and ask clarifying questions.
- Share your insights and participate in discussions.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice using the What-if Tool
Show steps
Complete the What-if Tool guided tutorials to gain hands-on experience with the tool's capabilities.
Show steps
Show steps
Show steps
- Follow the Google Cloud tutorial on using the What-if Tool.
- Work through the examples provided in the tutorial.
- Experiment with different scenarios using the What-if Tool.
Attend a workshop on AI ethics and bias mitigation
Show steps
Attend a workshop or seminar that focuses on the ethical implications of AI and techniques for mitigating bias. This will provide you with practical insights and best practices.
Show steps
Show steps
Show steps
Present your findings from the What-if Tool analysis
Show steps
Create a presentation or report that summarizes your findings from the What-if Tool analysis. This will help you solidify your understanding of the tool and its application.
Show steps
Show steps
Show steps
- Identify the key findings from your What-if Tool analysis.
- Organize your findings into a logical and coherent presentation.
- Create visuals and examples to illustrate your findings.
- Practice presenting your findings clearly and concisely.
Volunteer for a non-profit organization focused on AI ethics
Show steps
Apply your knowledge and skills by volunteering for an organization that promotes responsible AI development and addresses issues of bias and fairness.
Show steps
Show steps
Show steps
Create a blog post or article summarizing your learnings
Show steps
Write a blog post or article that summarizes the key concepts and insights you have gained from the course. This will help you solidify your understanding and communicate your knowledge to others.
Show steps
Show steps
Show steps
- Identify the main takeaways from the course.
- Organize your thoughts into a logical and coherent outline.
- Write a draft of your blog post or article.
- Revise and edit your writing for clarity and accuracy.
Career center
Learners who complete Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. This course can help Data Analysts build a foundation in using AI and machine learning to analyze data. This course can also help Data Analysts identify and mitigate bias in their data analysis.
Statistician
Statistician
Statisticians analyze data to find trends and patterns. They use their findings to help businesses make informed decisions. This course can help Statisticians build a foundation in using AI and machine learning to analyze data. This course can also help Statisticians identify and mitigate bias in their data analysis.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and build machine learning models. This course can help Machine Learning Engineers build a foundation in using AI and machine learning to analyze data. This course can also help Machine Learning Engineers identify and mitigate bias in their machine learning models.
Data Scientist
Data Scientist
Data Scientists use data to solve complex problems. This course can help Data Scientists build a foundation in using AI and machine learning to analyze data. This course can also help Data Scientists identify and mitigate bias in their data analysis.
Risk Analyst
Risk Analyst
Risk Analysts identify and assess risks to businesses. This course can help Risk Analysts build a foundation in using AI and machine learning to identify and assess risks. This course can also help Risk Analysts identify and mitigate bias in their risk analysis.
Product Manager
Product Manager
Product Managers develop and manage products. This course can help Product Managers build a foundation in using AI and machine learning to develop products. This course can also help Product Managers identify and mitigate bias in their products.
Actuary
Actuary
Actuaries use mathematics and statistics to assess risk and uncertainty. This course can help Actuaries build a foundation in using AI and machine learning to assess risk and uncertainty. This course can also help Actuaries identify and mitigate bias in their risk assessment.
Real Estate Agent
Real Estate Agent
Real Estate Agents help people buy and sell homes. This course can help Real Estate Agents build a foundation in using AI and machine learning to assess risk. This course can also help Real Estate Agents identify and mitigate bias in their risk assessment.
Compliance Analyst
Compliance Analyst
Compliance Analysts ensure that businesses comply with laws and regulations. This course can help Compliance Analysts build a foundation in using AI and machine learning to ensure compliance. This course can also help Compliance Analysts identify and mitigate bias in their compliance analysis.
Loan Officer
Loan Officer
Loan Officers help people get loans. This course can help Loan Officers build a foundation in using AI and machine learning to assess risk. This course can also help Loan Officers identify and mitigate bias in their risk assessment.
Mortgage Broker
Mortgage Broker
Mortgage Brokers help people get mortgages. This course can help Mortgage Brokers build a foundation in using AI and machine learning to assess risk. This course can also help Mortgage Brokers identify and mitigate bias in their risk assessment.
Underwriter
Underwriter
Underwriters assess risk and determine whether to approve insurance policies. This course can help Underwriters build a foundation in using AI and machine learning to assess risk. This course can also help Underwriters identify and mitigate bias in their risk assessment.
Business Analyst
Business Analyst
Business Analysts analyze business processes to identify opportunities for improvement. This course can help Business Analysts build a foundation in using AI and machine learning to analyze business processes. This course can also help Business Analysts identify and mitigate bias in their business analysis.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help Software Engineers build a foundation in using AI and machine learning to develop software systems. This course can also help Software Engineers identify and mitigate bias in their software systems.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. This course can help Financial Analysts build a foundation in using AI and machine learning to analyze financial data. This course can also help Financial Analysts identify and mitigate bias in their financial analysis.
For more career information including salaries, visit:
OpenCourser.com/course/xh8qjj/identifying
Reading list
We've selected eight 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
Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool.
Sutton and Barto's book classic and foundational text on reinforcement learning, providing a comprehensive overview of the field.
Hastie et. al provides a comprehensive treatment of statistical learning methods with a focus on sparsity, which is particularly important in high-dimensional data analysis.
A practical and accessible guide to deep learning, Howard and Gugger's book focuses on practical implementation with PyTorch and the fastai library.
Géron's book practical and comprehensive guide to machine learning with Python, covering topics such as data preprocessing, model selection, and evaluation.
Molnar's book bridges the gap between conceptual understanding and practical implementation by providing a comprehensive and practical treatment of interpretable machine learning models and techniques.
Brynjolfsson and McAfee take a comprehensive view of the impact of AI on society, economy, and employment, offering insights into the potential challenges and opportunities posed by AI.
Boyd and Vandenberghe's book provides a comprehensive introduction to convex optimization, which is fundamental to many machine learning algorithms.
Save
Marsland's book provides a theoretical foundation for machine learning algorithms, covering topics such as supervised learning, unsupervised learning, and reinforcement learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/xh8qjj/identifying
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Effort
1 hour
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Teaches how to identify biases in AI models, which is key for fairness and accountability in AI systems
Hands-on lab provides practical experience with real-world data, enhancing understanding and application of concepts
Conducted by Google Cloud Training, known for expertise and industry-leading practices in AI
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