AI Analytics for Builders
Shane Butler
Principal Data Scientist @ Ontra
Sravya Madipalli
Data Science Leader |Ex-Microsoft
This course is popular
26 people enrolled last week.
Ask Better Questions, Make Faster Decisions - with AI as Your Analyst
Cohort 1 is in Session, but it's not too late to enroll!! Kick off was April 20. Final registration closes April 27. Everything has been recorded so you don't miss a thing!
As AI reduces the value of deep domain silos, the people who thrive will be the ones who can work across disciplines and ship.
Analytical independence - the ability to validate your own ideas and make data-informed decisions - remains the missing skill in most builders' toolkits.
AI can conduct the analysis, but it can't tell you what to ask or whether the answer makes sense. That requires analytical judgment.
This course teaches you to think like a senior Product Data Scientist. You'll learn the frameworks used at FAANG companies to frame problems, choose the right metrics, diagnose root causes, execute the analysis, and turn insights into decisions.
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What makes this different: No SQL. No stats lectures. Five weeks of hands-on real scenarios. You'll build end-to-end, metric specs, deep dives, experiment plans, stakeholder readouts.
The result: You become analytically self-sufficient. The last dependency removed from your toolkit. Make data-informed decisions in hours, not weeks.
What you’ll learn
Transform from consumer of analytics to independent operator - asking sharp questions, validating answers, shipping decisions.
Transform vague ideas into decision-forcing questions.
Distinguish good analytical questions from time-wasting ones using a 3-part framework.
Build a ranked list of analytical questions by expected impact - so you always know what to analyze first.
Define numerators, denominators, time windows, and edge cases so your team never debates "what this number really means" again.
Build metric trees that decompose north star metrics into actionable drivers - separating guardrails from success metrics.
Use AI to draft comprehensive metric specs, generate segment cuts, and run QA checks that catch ambiguity before it breaks trust.
Decompose metric changes into mix shift vs within-segment change - so you know if the problem is who showed up or what they did.
Use funnel debugging and cohort analysis to isolate the real drivers, not just correlations that look interesting but don't matter.
Generate hypothesis trees with AI, then systematically rule them out with evidence - turning "something changed" into "here's why."
Write testable hypotheses with clear success criteria and decision rules.
Leave with an Experiment Brief ready for your product development team.
Use AI to accelerate analysis while validating every output.
Leave with a complete capstone: problem brief to stakeholder readout.
Synthesize analytical findings into strategic recommendations with clear priorities.
Leave with a data-backed roadmap executives trust.
Learn directly from expert instructors
Shane Butler
Principal Data Scientist @ Ontra | Ex-Stripe, Nextdoor, PwC, Appfolio
Sravya Madipalli
Data Science Leader@Superhuman (Prev. Grammarly)| Ex-Microsoft, eBay, Nextdoor
Hai Guan
Head of Data @ Ontra | Ex-Nextdoor, LinkedIn, Pinterest, Meta
Who this course is for
Product Managers, engineers, and operators who need analytical independence and frameworks to measure success and drive decisions.
Designers and researchers stepping into strategy roles who need to quantify impact, run experiments, and influence with data-driven insights
Data professionals who want to frame better questions, delegate technical execution to AI, and drive impact with agentic analytics tools.
What's included
Live sessions
Learn directly from your instructors in a real-time, interactive format.
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
Course syllabus
15 live sessions • 44 lessons • 2 projects
Week 1
Apr
20
Kick-off!!!
Week 1 Resources
Foundations – Thinking Like a Product Data Scientist
Apr
22
Live Office Hour
Apr
24
Live Office Hour
Submissions
Week 2
Apr
27
Week 2 Launchpad
AI-Powered Analysis Fundamentals – Claude Code & Your Analytical Toolkit
AI Analytics Hands-On Practice
Apr
29
Live Office Hour
May
1
Live Office Hour
Schedule
Live sessions
2-3 hrs / week
Office Hours
Mon, Apr 20
3:00 PM—4:00 PM (UTC)
Wed, Apr 22
12:00 AM—1:00 AM (UTC)
Fri, Apr 24
2:00 PM—3:00 PM (UTC)
Projects
2-3 hrs / week
Capstone Project
Async content
3-4 hrs / week
Recorded Lessons
Frequently asked questions
$1,800
USD
4 days left to enroll