Cohort Program

AI Analytics for Everyone (1 Session Per Week)

Ask Better Questions, Make Faster Decisions - with AI as Your Analyst

Overview

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. -> Join AI Builders Slack Community!! <- 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

Frame Problems Like a Senior Data Scientist 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.
Design Metrics That Actually Drive Decisions 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.
Design Experiments That Ship Write testable hypotheses with clear success criteria and decision rules. Leave with an Experiment Brief ready for your product development team.
Turn Analysis Into Action With AI as Your Copilot Use AI to accelerate analysis while validating every output. Leave with a complete capstone: problem brief to stakeholder readout.

Schedule

5 weeks, 5 live sessions, one each week. The first is 14 Sept 2026, 12:45 AM GMT+8, and they run weekly after that.
Every session is recorded. You keep the recording for 30 days after each one, so you can catch up if you ever miss one live.

Curriculum

5 weeks · 5 live sessions · tap a week to see what you build

Week1Session 113 Sept 2026
Understanding AI powered analytics: from data to decisions
Introduction to AI Analytics Pre-work: Read an introduction to AI assisted analytics and install the required AI and spreadsheet tools.
BuildImport a dataset, identify key business questions, and use AI to generate an initial analysis and summary.
ReviewedInstructor reviews the business questions, data preparation, and the quality of AI generated insights.
Week2Session 220 Sept 2026
Data Cleaning, Exploration & Visualization Pre-work: Watch a tutorial on preparing data for analysis and review common visualization techniques.
Data Cleaning, Exploration & Visualization Pre-work: Watch a tutorial on preparing data for analysis and review common visualization techniques.
BuildClean a messy dataset, explore trends with AI, and create meaningful charts and visualizations.
ReviewedReviewed for data quality, appropriate visualizations, and the ability to identify patterns and anomalies.
Week3Session 327 Sept 2026
AI Powered Business Insights Pre-work: Read a case study on using analytics to solve business problems.
AI Powered Business Insights Pre-work: Read a case study on using analytics to solve business problems.
BuildAnalyze a real business scenario, generate AI assisted insights, and recommend actions supported by data.
ReviewedInstructor evaluates the relevance of insights, reasoning behind recommendations, and clarity of communication.
Week4Session 404 Oct 2026
Dashboards & Automated Reporting Pre-work: Explore examples of executive dashboards and AI generated reports.
Dashboards & Automated Reporting Pre-work: Explore examples of executive dashboards and AI generated reports.
BuildBuild an interactive dashboard and create an executive summary using AI for a chosen dataset.
ReviewedDashboard usability, visual storytelling, report quality, and presentation of key metrics are reviewed.
Week5Session 511 Oct 2026
Capstone: End to End AI Analytics Project Pre-work: Refine previous assignments and prepare a short presentation.
Capstone: End to End AI Analytics Project Pre-work: Refine previous assignments and prepare a short presentation.
BuildComplete a full analytics project by cleaning data, generating insights, building a dashboard, and presenting actionable business recommendations.
ReviewedFinal evaluation includes a live presentation, dashboard demonstration, AI workflow, business impact, and instructor plus peer feedback.

What you'll build

An AI powered analytics dashboard A reusable data analysis workflow

How your work is reviewed

Each week you ship it to me. I review and give a written feedback

Capstone

Participants will analyze a real world dataset using AI, uncover meaningful insights, create a dashboard, and present data backed recommendations for a business scenario.

About Cena

Cena John

Vetted by Maram

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Reviews

Reviews appear here once 3 learners have completed this session.

Free resource

9 Pages AI Analytics Automation

Tips to build AI Analytics

FAQ

Who is this cohort designed for?

It is built for builders, product managers, founders, and others who make decisions and want to validate their own ideas with data, without relying on a dedicated analyst. If you have shipped something or are actively building, you are the target audience.

Do I need to know SQL, statistics, or data science before joining?

No. The program is designed to work without SQL or statistics lectures, using AI to handle the technical execution so you can focus on developing analytical judgment and framing the right questions.

What does the program actually look like week to week?

It runs over five weeks and is hands-on throughout, built around real scenarios rather than theory. You will work through metric specs, deep dives, experiment plans, and stakeholder readouts from start to finish.

What will I be able to do by the end that I cannot do now?

You will be able to frame analytical problems, choose the right metrics, diagnose root causes, run your own analysis with AI, and present findings to stakeholders, without waiting on someone else to do it for you.

Is there a community component?

Yes, participants get access to an AI Builders Slack community as part of the program.

How is this different from a data analytics course I could take elsewhere?

The focus is on analytical thinking and judgment rather than technical skills like coding or statistics, and every week is grounded in practical scenarios rather than lectures. The goal is to make you self-sufficient, not to train you to become a data scientist.