Data Analysis with Generative AI
Generative AI is reshaping how analysts extract insights from data—and you need to know how to use it. This 43-minute course shows you exactly where AI accelerates analysis workflows, what it can and can’t do, and how to integrate it into your toolkit without the hype.
AIU.ac Verdict: Ideal for analysts, business intelligence professionals, and data practitioners who want to understand generative AI’s real role in their work. The course is deliberately compact, so expect focused essentials rather than deep-dive theory—perfect for busy professionals, but not for those seeking advanced model customisation.
What This Course Covers
You’ll explore how generative AI augments traditional data analysis: prompt engineering for data queries, using AI to accelerate exploratory data analysis, automating routine reporting tasks, and recognising where human judgment remains essential. The course balances practical demonstrations with honest assessment of AI’s limitations in statistical rigour and domain expertise.
David Clinton walks through real-world scenarios where generative AI adds genuine value—pattern spotting, hypothesis generation, and narrative synthesis—alongside the pitfalls of over-reliance on AI outputs. You’ll leave with a clear mental model of where to deploy AI in your analysis pipeline and where to keep humans in control.
Who Is This Course For?
Ideal for:
- Data analysts and BI professionals: Want to understand how generative AI changes their daily workflows without learning to build models.
- Business intelligence managers: Need to evaluate AI tools for their teams and understand realistic ROI and risk.
- Career-switchers into analytics: Starting their journey and want to learn modern tools from day one rather than legacy-first approaches.
May not suit:
- Machine learning engineers: Seeking technical depth on model architecture, fine-tuning, or prompt optimisation—this is practitioner-focused, not engineering-focused.
- Absolute beginners to data: Without foundational knowledge of data concepts, analysis methods, or SQL; this assumes you already work with data.
Frequently Asked Questions
How long does Data Analysis with Generative AI take?
43 minutes. It’s designed for busy professionals who need practical insights without lengthy theory.
Do I need coding experience?
No. The course focuses on how to use generative AI tools within analysis workflows, not on writing code. Basic familiarity with data analysis concepts is helpful.
Who is David Clinton?
A Pluralsight-vetted author (top 5.5% acceptance rate). Clinton specialises in practical, no-nonsense tech training for working professionals.
Will this teach me to build AI models?
No. This course teaches you how to *use* generative AI as an analyst. If you want to build or fine-tune models, you’ll need a dedicated machine learning course.
Course by David Clinton on Pluralsight. Duration: 0h 43m. Last verified by AIU.ac: March 2026.
