Prepare data for reliable AI work
Collection, quality, labeling, leakage, privacy, evaluation sets, and monitoring.
What you will be able to do
Create a small evaluation dataset without leaking sensitive or target information.
Included tools
No specific tool required.
Content map
See what you will learn—and whether the lessons are genuinely available or still an outline.
This is an editorial outline for candidate content. Its titles are not published lessons and may change after review.
Orient yourself4 lessons
- The Modern Data Analyst: AI as a PartnerOutline only — lesson not published
- Advanced Data Analysis in ChatGPTOutline only — lesson not published
- Interactive Dashboards with Claude ArtifactsOutline only — lesson not published
- AI-Powered Google Sheets IntegrationOutline only — lesson not published
Do the work3 lessons
- Microsoft Copilot: Python inside ExcelOutline only — lesson not published
- Specialized Platforms: Julius AI & BeyondOutline only — lesson not published
- Practical Workflow: Clean and Model Sales DataOutline only — lesson not published
Review and apply3 lessons
- Common AI Analytics Pitfalls & MitigationOutline only — lesson not published
- Data Tools Comparison MatrixOutline only — lesson not published
- Summary: The AI Data Analyst's ChecklistOutline only — lesson not published