AI Data Analysis for Non-Data People
Nicky Bell, PhD
3x greenfield data scientist
PhD-level judgment, without the PhD-level pain.
You're a team of one—a solopreneur, bootstrapper, or BizOps operator—expected to analyze and report data, without an analyst to lean on.
You can build a spreadsheet, but you have no formal data training and don't see yourself as a "data person."
You looked at other courses and they all wanted to teach you to code.
This course teaches the judgment that makes AI-generated analysis trustworthy. You'll see blind spots, ask sharper questions, and become the operator the C-suite trusts when AI is on the agenda.
*****
🎓 What You'll Get
1:1 coaching — 30 minutes to map your organization's data challenges and leave
with an actionable blueprint.
Live audits of real AI-generated outputs — submit a report from your own data and watch 2–3 anonymized examples get evaluated and rebuilt, live.
More than 7 hours of professionally-produced video + classroom instruction.
What you’ll learn
Ask the right questions and spot the hidden landmines in AI data analysis -- without code or math.
Diagnose who or what is missing from a dataset using judgment, not statistics.
Tell when a confident AI result is actually just a guess dressed up as fact.
Recognize when the right move is to walk away from the analysis entirely.
Tell AI what good looks like before it calculates a single number.
Write prompts like you're briefing a new hire — context first, task second.
Make AI surface its doubts, not just its answers.
Apply three frameworks for separating correlation from causation in real-world contexts.
Recognize the alternative explanation AI didn't surface — and put it back on the table.
Translate "this didn't drive that" into language any executive accepts on the spot.
Submit an AI-generated report from your actual work and watch 2–3 anonymized examples get audited live.
Pattern-match across your cohort's real submissions, not hypothetical case studies.
Get early access to Circuit — automated AI data validation tool you can use on any analysis
Watch your seat at the table grow as roles consolidate around AI.
Build your reputation every time you catch what AI got wrong.
Stop outsourcing the data conversation and start owning it.
Learn directly from Nicky
Nicky Bell, PhD
10 years teaching data literacy to up-and-coming data operators
Who this course is for
Bootstrappers, solopreneurs, and teams-of-one responsible for guiding data-driven decisions without a dedicated analyst counterpart.
Operators who want to leverage AI for data analysis, but don't know how to trust the results.
Anyone who has ever said, "I'm not a data person." Data isn’t about code or math. Data is about judgment, and judgment can be learned.
Prerequisites
Curiosity about the process of data analysis, not just outputs.
We'll take a first-principles approach to data analysis. You'll learn the mindset of a data person -- and the outputs will follow naturally.
Basic familiarity with AI tools.
If you've used ChatGPT, Claude, or any LLM for simple tasks like summarizing notes, you're ready.
Access to some data.
We'll provide datasets for examples, but you'll get more value applying these concepts to your own work.
What's included
Live sessions
Learn directly from Nicky Bell, PhD in a real-time, interactive format.
1:1 coaching
30 minutes to map the specific data challenges in your organization. You'll leave with an actionable blueprint for how to position yourself as the expert in the room when AI analysis is on the agenda.
Live audits of real AI-generated outputs
Submit an AI-generated report from your actual work and watch 2–3 anonymized examples get audited live.
Professionally-produced video instruction
Learn on your schedule with high-quality instructional videos, with loads of real-world examples
Early access to Circuit — automated AI data validation tool
Apply your new skills with the click of a button using Powered Analysis' AI data validation tool. Free for Founding Cohort members.
Bonus content — exclusively for Maven students
Continue your learning journey after the course ends
Lifetime access to videos and recordings
Go back to course content and recordings whenever you need to.
100% Risk-Free guarantee
Get a 100% refund if you’re not satisfied with the course.
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
Course syllabus
Week 1
💯 How to count what matters
🕵️ How to spot selection bias - and fix it
🤔 What "correlation does not equal causation" actually means
Week 2
☺️ How to embrace uncertainty instead of hiding from it
😶🌫️ How to find what's missing - and if it matters
📈 How to avoid dangerous defaults in data visualization.
🛠️ Project: Submit your own AI data analysis for a live audit
Free resource
Catch Three AI Analysis Errors -- Before You Run The Numbers
How to count what actually matters 💯
Four criteria that separate good metrics from a misleading ones.
Spot bias in your data that no math can fix 🕵️♀️
Recognize when data was collected in ways that quietly distort answers and lead to wrong decisions.
Whether your data shows causes, not just correlations 📈
Three frameworks to know when the data is telling you the next right move for your org.
Schedule
Live sessions
1 hr / week
Watch live audits of real AI-generated data analyses; learn to communicate data for impact; practice critiquing data analysis with your peers.
Async videos to learn on your own schedule
1-2 hrs / week
Professionally-produced and expert-reviewed content to prepare you for live sessions.
Frequently asked questions
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