In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models.
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Ethics in the Age of AI 专项课程LearnQuest课程信息
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第 2 门课程（共 4 门）
初级
完成时间大约为6 小时
英语（English）
字幕：法语（French）, （欧洲人讲的）葡萄牙语, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）, 日语
您将获得的技能
- machine learning fairness
- Ethics
- data bias
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 2 门课程（共 4 门）
初级
完成时间大约为6 小时
英语（English）
字幕：法语（French）, （欧洲人讲的）葡萄牙语, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）, 日语
提供方
LearnQuest
LearnQuest is the preferred training partner to the world’s leading companies, organizations, and government agencies. Our team boasts 20+ years of experience designing, developing and delivering a full suite industry-leading technology education classes and training solutions across the globe. Our trainers, equipped with expert industry experience and an unparalleled commitment to quality, facilitate classes that are offered in various delivery formats so our clients can obtain the training they need when and where they need it.
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完成时间为 2 小时
Fairness and protections in machine learning
Welcome to the course! In week one, we will be discussing what fairness means in the context of machine learning and what true parity means in different scenarios
完成时间为 2 小时
5 个视频 （总计 19 分钟）, 2 个阅读材料, 3 个测验
完成时间为 2 小时
Building fair models: theory and practice
This week we will take action against unfairness. Now that we have an understanding of fairness issues, how do we build models that do not violate them?
完成时间为 2 小时
5 个视频 （总计 21 分钟）, 2 个阅读材料, 3 个测验
完成时间为 2 小时
Human factors: minimizing bias in data
This week, we will tackle the human biases that enter the data collection and attribute selection processes. The goal? Removing bias before the model is built
完成时间为 2 小时
5 个视频 （总计 33 分钟）, 2 个阅读材料, 3 个测验
审阅
- 5 stars82.85%
- 4 stars14.28%
- 3 stars2.85%
来自ARTIFICIAL INTELLIGENCE DATA FAIRNESS AND BIAS 的热门评论
由 AV 提供Jan 14, 2021
Extraodinary course! I've learnt so much! The classes are very informative and dynamic. Didn't feel like studying but rather entertaining myself with hight quality content! Thank you so much!
由 SY 提供Mar 30, 2021
A relatively short and interesting course on data fairness and bias impacting AI models.
由 CM 提供Oct 2, 2021
An excellent reminder that the bias-variance trade-off is not the only trade-off machine learning specialists make.
由 RU 提供Apr 19, 2022
Really great discussion of algorithms and how their designs make them susceptible to bias.
关于 Ethics in the Age of AI 专项课程
As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations. In this specialization, we will explore the rise of algorithms, fundamental issues of fairness and bias in machine learning, and basic concepts involved in security and privacy of machine learning projects. We'll finish with a study of 3 projects that will allow you to put your new skills into action.
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