AI for Data Analytics

• Use AI tools to clean, explore, analyze, visualize, and report on datasets.
• Write stronger prompts for data work using a simple analytical prompt framework.
• Validate AI-generated results with a structured 7-step checklist.
• Build and evaluate predictive models through natural language, without coding.
• Document your workflow with an AI Traceability Document for accountability and reproducibility.
• Present and defend AI-assisted findings in professional settings.
• Read a forecast for its uncertainty rather than its headline number, and know the four things that quietly break one
• Get themes and sentiment out of thousands of free-text comments, and run the check that decides whether to believe them
• Catch the harder errors that survive a first check: fabricated figures, trends that reverse when you split the data, and models that memorized instead of learned

• Open to beginners. Students must be comfortable using a computer; no other prior knowledge is required.

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