AI projects succeed or fail on the strength of their data. In this course, you’ll learn to diagnose pipeline bottlenecks, enforce governance standards, and plan data workflows that keep projects on track. Through real-world scenarios, you’ll trace issues like stale feature vectors, audit data handling for compliance with regulations such as General Data Protection Regulation (GDPR), and design actionable plans for data acquisition, storage, and annotation. You’ll also practice translating technical findings into project-ready deliverables, like drafting a Jira epic for large-scale data labeling.
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

您将获得的技能
- Data Storage
- Regulation and Legal Compliance
- General Data Protection Regulation (GDPR)
- Data Ethics
- Data Quality
- Data Governance
- Compliance Auditing
- Jira (Software)
- Personally Identifiable Information
- Dataflow
- Process Analysis
- Data Processing
- Project Planning
- Data Strategy
- Data Pipelines
- Data Management
- Performance Analysis
- Technical Communication
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

该课程共有1个模块
AI projects succeed or fail on the strength of their data. In this course, you’ll learn to diagnose pipeline bottlenecks, enforce governance standards, and plan data workflows that keep projects on track. Through real-world scenarios, you’ll trace issues like stale feature vectors, audit data handling for compliance with regulations such as General Data Protection Regulation (GDPR), and design actionable plans for data acquisition, storage, and annotation. You’ll also practice translating technical findings into project-ready deliverables, like drafting a Jira epic for large-scale data labeling.
涵盖的内容
6个视频3篇阅读材料4个作业
位教师

提供方
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