AI for data analytics

About this course

This course is about using AI in an analyst's daily work without losing control of the result: from framing a question and generating SQL to checking data and guarding your conclusions against self-deception. It solves the problem of speeding up routine work without losing analytical rigor.

The course moves from framing a checkable question and reading generated queries through table profiling and root-causing a metric drop to confidence intervals and report writing. Projects run on your own data marts: rebuild a working report through the query-generation process, bring a data mart to a state where breakage is caught before the stakeholder sees it, dissect a real metric change your team is currently debating.

Built for analysts and data people who already write SQL and build reports and want to fold AI into their work deliberately. You'll need basic SQL and hands-on experience working with data tables.

What you'll learn

• Turn a stakeholder request into a checkable question
• Describe a task to AI so it produces working SQL
• Spot common generation errors: joins, duplicates, dates
• Profile a table and find gaps, duplicates, and late-arriving data
• Root-cause a metric drop step by step without jumping to conclusions
• Tell a meaningful difference apart from sampling noise
• Explain confidence intervals in plain terms
• Write a report that moves from numbers to conclusions and decisions

What you'll end up with

• A rebuilt working report produced through a query generation and verification process
• A data mart with tests that catch breakage before it reaches stakeholders
• A dissected real metric change, checked against self-deception
• A certificate on paid plans

Not for you if you don't work with tables and SQL and are looking for a from-scratch programming course.