Applications Opening Soon

Learn Data.
Apply It.
Defend It.

A selective, simulation-based program that turns data learners into professionals — through real briefs, real analysis, and boardroom-style presentations.

4× Industry Simulations
<20 Per Cohort
100% Portfolio-Ready
✓ Cohort 01 — Completed
📉
Revenue Leak Analysis Identifying and quantifying revenue loss across business units
Done
4 briefs completed · Boardroom defended · Portfolios shipped
Cohort 02 — Applications Opening Soon
🏦
Customer Churn Prediction Retention modelling for a high-growth fintech
Brief 01
🛒
Supply Chain Demand Forecasting Inventory optimisation across distribution nodes
Brief 02
🏥
Marketing Spend Attribution ROI analysis across channels for a consumer brand
Brief 03
📊
Operational Efficiency Audit Process bottleneck analysis for a logistics company
Brief 04
Fintech Analysis E-commerce Insights Boardroom Presentations Healthcare Data Business Intelligence Data Storytelling Logistics Analytics Marketing Analytics Executive Briefings Portfolio Projects Fintech Analysis E-commerce Insights Boardroom Presentations Healthcare Data Business Intelligence Data Storytelling Logistics Analytics Marketing Analytics Executive Briefings Portfolio Projects
The Gap

You know the tools.
But can you use them?

Many data learners complete courses, learn Python and SQL, follow every tutorial — and still can't answer the one question that matters in every interview:

"Do you have real experience solving business problems with data?"

Most don't. Data Starter NG exists to change that.

Four phases.
Real experience.

A structured journey from foundational refresh to portfolio-ready professional, with feedback at every stage.

01
Week 1–2

Foundations Refresh

Align on core analytical skills before the simulations begin — data cleaning, EDA, business framing, and storytelling. No filler.

02
Week 3–5

Industry Simulation

Receive a real business brief and dataset. Step into the role of a data consultant and generate insights that actually matter.

03
Week 6

Boardroom Presentation

Present findings to a simulated executive panel. Answer tough questions. Defend your analysis under pressure — just like the real thing.

04
Post-Cohort

Portfolio & Experience

Every simulation becomes a documented, portfolio-ready case study. Leave with proof of your capabilities — not just a certificate.

Built for learners ready to take
the next step.

Designed for people who already have foundational data skills and want to translate knowledge into real-world capability.

📊
Aspiring Data Analysts You know SQL and Excel. You need proof you can apply them to real business problems.
🐍
Data Science Learners You've done Python courses. Now apply that on real, messy business data.
🔁
Career Switchers Transitioning into data? Build a credible portfolio before your next application.
🎓
University Students Stand out from peers with real project experience before you graduate.

Not for complete beginners. Build your foundation first — then come back when you're ready.

Leave with skills that
show, not tell.

Real problem-solving experience — not toy datasets, not guided notebooks

Portfolio-worthy case studies — projects you built and actually defended

Stakeholder communication skills — present and defend insights with confidence

Cross-industry exposure — fintech, e-commerce, healthcare, logistics, and more

Mentorship and structured feedback — from professionals who've done the work

A peer network — a selective community of serious, committed practitioners

Small by design.
Serious by default.

Data Starter NG runs in small, selective cohorts. Every participant goes through an application process — because the quality of your peers is part of the program.

You won't find passive learners here. Everyone in the room is committed to growing.

<20 Participants per cohort
100% Online & flexible
4 Industry simulations
1:1 Mentorship included

Express Interest in the Next Cohort

Applications are opening soon. Drop your details and be the first to know — plus get early access before spots are filled.

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