Document and Evaluate AI Ethics is an intermediate course that equips engineers, auditors, and AI practitioners with the concrete skills to move from ethical principles to engineering practice. You will learn to create comprehensive model cards that document a system's intended use, dataset origins, performance metrics, and limitations, ensuring every stakeholder understands what the system does and where it might fail.

Document and Evaluate AI Ethics
本课程是多个项目的一部分。

位教师:LearningMate
访问权限由 New York State Department of Labor 提供
您将学到什么
Create comprehensive documentation and conduct ethical evaluations of large language model systems to ensure responsible AI deployment.
您将获得的技能
- Compliance Auditing
- Project Documentation
- Accountability
- Data Ethics
- Compliance Management
- Case Studies
- Auditing
- Ethical Standards And Conduct
- Business Ethics
- Model Evaluation
- Model Deployment
- MLOps (Machine Learning Operations)
- Technical Documentation
- Data Quality
- Responsible AI
- Mitigation
- 技能部分已折叠。显示 10 项技能,共 16 项。
要了解的详细信息
了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书

该课程共有2个模块
Have you ever released an AI feature only to realize no one could clearly explain what it does or where its data came from? That gap begins with missing documentation. This module shows how structured model cards build trust and accountability. You will capture a model’s purpose, dataset origins, fairness metrics, and limits, creating documentation that speaks to both engineers and stakeholders and keeps AI systems transparent.
涵盖的内容
2个视频3篇阅读材料1个作业1个非评分实验室
Have you ever seen an AI output that felt biased or off and wondered what caused it? Ethical issues often hide in oversight, not code. This module shows how to identify and address those risks before they escalate by applying structured audit frameworks to evaluate fairness and compliance in AI systems.
涵盖的内容
2个视频1篇阅读材料2个作业1个非评分实验室
获得职业证书
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