Coursera
Strategic AI Governance 专项课程

只需 199 美元(原价 399 美元)即可通过 Coursera Plus 学习更高水平的技能。立即节省

Coursera

Strategic AI Governance 专项课程

Lead AI Governance and Responsible Deployment. Build expertise in AI ethics, governance frameworks, and operational excellence for enterprises.

Caio Avelino
Starweaver
Karlis Zars

位教师:Caio Avelino

包含在 Coursera Plus

深入学习学科知识
中级 等级

推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入学习学科知识
中级 等级

推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Design and implement comprehensive AI governance frameworks with ethical guidelines, risk assessments, and compliance policies.

  • Build and automate secure MLOps pipelines while conducting systematic audits for bias, fairness, and responsible AI deployment.

  • Optimize AI operations through cloud cost management, security assessments, and performance monitoring across enterprise systems.

要了解的详细信息

可分享的证书

添加到您的领英档案

授课语言:英语(English)
最近已更新!

December 2025

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

精进特定领域的专业知识

  • 向大学和行业专家学习热门技能
  • 借助实践项目精通一门科目或一个工具
  • 培养对关键概念的深入理解
  • 通过 Coursera 获得职业证书

专业化 - 7门课程系列

您将学到什么

  • Evaluate AI use cases by applying key Responsible AI principles such as fairness, transparency, and accountability.

  • Identify and document potential risks and biases across data, models, and user interactions using structured ethical design tools.

  • Develop and communicate stakeholder-ready presentations and documentation that clearly articulate Responsible AI design decisions.

您将获得的技能

类别:Stakeholder Communications
类别:Responsible AI
类别:Ethical Standards And Conduct
类别:Case Studies
类别:Stakeholder Analysis
类别:Accountability
类别:Technical Communication
类别:Design
类别:Presentations
类别:Artificial Intelligence
类别:Data Storytelling
类别:Data Ethics
类别:Governance
类别:Risk Management
类别:Risk Mitigation
类别:Project Documentation

您将学到什么

  • Performance monitoring is essential for maintaining AI system reliability and fairness across diverse user populations

  • Technical architecture decisions (fine-tuning vs RAG) require systematic evaluation of costs, capabilities, and maintenance requirements

  • Effective AI governance requires proactive policy creation, technical guardrails, and cross-functional collaboration to ensure responsible deployment

  • Sustainable AI operations depend on establishing measurable quality benchmarks and continuous feedback loops

您将获得的技能

类别:Risk Management
类别:Large Language Modeling
类别:Prompt Engineering
类别:Gap Analysis
类别:Data-Driven Decision-Making
类别:Performance Metric
类别:Performance Analysis
类别:AI Security
类别:Governance
类别:Model Evaluation
类别:Responsible AI
类别:System Monitoring
类别:Cost Benefit Analysis
类别:Content Performance Analysis
类别:Governance Risk Management and Compliance
类别:Retrieval-Augmented Generation
类别:Quality Assessment
类别:Cross-Functional Team Leadership
类别:Compliance Management
类别:Generative AI
Govern Your GenAI Data Safely

Govern Your GenAI Data Safely

第 3 门课程2小时

您将学到什么

  • Learners will be able to systematically analyze data access patterns to recommend role-based controls, evaluate organizational governance maturity ag

您将获得的技能

类别:Governance
类别:Data Management
类别:Data Governance
类别:Data Quality
类别:Data Security
类别:Quality Assurance and Control
类别:Benchmarking
类别:Role-Based Access Control (RBAC)
类别:Generative AI
类别:Responsible AI
类别:Data Access
类别:Identity and Access Management
类别:AI Security
类别:SQL
类别:Metadata Management

您将学到什么

您将获得的技能

类别:Technology Roadmaps
类别:Organizational Strategy
类别:Data Ethics
类别:Business Ethics
类别:Governance
类别:Decision Making
类别:Enterprise Architecture
类别:Risk Analysis
类别:Artificial Intelligence and Machine Learning (AI/ML)
类别:Artificial Intelligence
类别:Cross-Functional Collaboration
类别:Responsible AI
类别:Data Governance
类别:Strategic Leadership

您将学到什么

  • Reliable MLOps depends on systematic diagnosis: performance issues are solved by log analysis and pipeline investigation, not guesswork.

  • Governance must be automated into deployment—responsible AI needs CI/CD checks for fairness, explainability, and safe rollbacks, not manual reviews.

  • Adaptive systems need intelligent automation—production models should monitor drift and trigger retraining automatically to stay accurate.

  • Operational excellence requires end-to-end visibility, strong monitoring, versioning and audit trails enable fast debugging and long-term reliability

您将获得的技能

类别:Continuous Monitoring
类别:Continuous Delivery
类别:Continuous Deployment
类别:Data Pipelines
类别:Model Evaluation
类别:CI/CD
类别:MLOps (Machine Learning Operations)
类别:Data Governance
类别:Model Deployment
类别:Responsible AI
类别:Continuous Integration
类别:Cloud Platforms
类别:Performance Analysis
类别:Automation
类别:Performance Tuning
Document and Evaluate AI Ethics

Document and Evaluate AI Ethics

第 6 门课程3小时

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

类别:Auditing
类别:Responsible AI
类别:Data Ethics
类别:Technical Documentation
类别:Model Deployment
类别:Mitigation
类别:Data Quality
类别:Accountability
类别:Business Ethics
类别:Compliance Management
类别:Project Documentation
类别:MLOps (Machine Learning Operations)
类别:Compliance Auditing
类别:Ethical Standards And Conduct
类别:Model Evaluation
类别:Case Studies
Measure ML Impact & Business Value

Measure ML Impact & Business Value

第 7 门课程4小时

您将学到什么

  • Map model metrics to business metrics, and define baselines, counterfactuals, and a measurement plan.

  • Design experiments, compute lift and confidence intervals, and plan guardrails.

  • Quantify ROI and risk, build an impact dashboard, and craft an executive story with clear next steps.

您将获得的技能

类别:Business Metrics
类别:A/B Testing
类别:Dashboard
类别:Return On Investment
类别:Machine Learning
类别:Performance Measurement
类别:Financial Analysis
类别:Business
类别:Model Evaluation
类别:Key Performance Indicators (KPIs)
类别:Power Electronics
类别:Performance Analysis
类别:Experimentation
类别:Stakeholder Communications
类别:Sample Size Determination
类别:Data Storytelling
类别:Product Management
类别:Analysis
类别:Business Valuation

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Caio Avelino
7 门课程7,135 名学生
Starweaver
Coursera
511 门课程925,886 名学生
Karlis Zars
32 门课程53,118 名学生

提供方

Coursera

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.
自 2018开始学习的学生
''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情,我就可以学习。'
Jennifer J.
自 2020开始学习的学生
''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'
Larry W.
自 2021开始学习的学生
''如果我的大学不提供我需要的主题课程,Coursera 便是最好的去处之一。'
Chaitanya A.
''学习不仅仅是在工作中做的更好:它远不止于此。Coursera 让我无限制地学习。'

常见问题