MODULE 1

Course Overview and Study Method for Data Work

Transform the course from catalog to cognitive system, with study method, technical memory, and professional output plan.

How to Study This Course Well - official lesson image on GinnyTech, created by AD

Base 18 min

How to study technical material without forgetting it

Il protocollo 40-10-10 per studiare materiale tecnico: comprensione, richiamo attivo e artefatto, con richiami D+1, D+3 e D+7 e il test del foglio bianco contro la curva dell'oblio.

Prerequisites: 1

Go to lesson

How This Course Works - official lesson image on GinnyTech, created by AD

Base 18 min

'First principles: how a strong analyst thinks'

Il pensiero per primi principi applicato ai dati: cinque blocchi (decisione, ipotesi, misura, guardrail, output) e le Cinque Perché per risalire alla causa radice prima di decidere.

Prerequisites: 1

Go to lesson

How to Practice on Data While Studying - official lesson image on GinnyTech, created by AD

Base 18 min

From Business Question to Analytical Question

Tradurre una domanda di business in domanda analitica con decisione, confronto, metrica e soglia, fissando la soglia prima di guardare i dati e scrivendo il template delle quattro righe.

Prerequisites: 1

Go to lesson

How to Take Notes Without Getting Lost - official lesson image on GinnyTech, created by AD

Base 18 min

How to take technical notes, version ideas, and build memory

Note atomiche in cinque blocchi, collegamenti tra idee e doppio passaggio: come costruire una memoria esterna navigabile e versionata con markdown e git.

Prerequisites: 1

Go to lesson

How to Really Remember What You Learn - official lesson image on GinnyTech, created by AD

Base 18 min

'Reproducibility mindset: rigor before speed'

Il reproducibility mindset in tre pilastri: tracciabilità, standard e revisionabilità, per rendere ogni output ricostruibile da altri e misurare il tasso di analisi riproducibili.

Prerequisites: 1

Go to lesson

Base 18 min

From course to work skills

How to turn course knowledge into practical skills marketable in the job market.

Prerequisites: 1

Go to lesson

How Not to Lose Motivation in the Long Term - official lesson image on GinnyTech, created by AD

Base 18 min

Initial skill diagnostic and personalized study plan

Skill diagnostic iniziale, ROI priority ranking e ciclo settimanale in quattro fasi: come costruire un piano di studio che rende visibile il progresso.

Prerequisites: 1

Go to lesson

Concept Maps: How to Navigate the 21 Course Modules - official lesson image on GinnyTech, created by AD

Base 8 min

Concept Maps: How to Enter the 21 Modules of the Course

Professional map of the GinnyTech course: 21 modules and 236 core lessons to navigate fundamentals, applications, technical stack, analytical rigor, and AI data work.

Prerequisites: 1

Go to lesson

Module connections

Continue the path with these modules

Same stage of the pathData Collection & Tracking Systems8 lessons

Move from isolated tags and tools to reliable, governed, and observable measurement systems.

Same stage of the pathMetrics, KPI Trees, and Analytical Foundations6 lessons

Learn to read numbers as systems, with KPI trees, unit economics, correct baselines, and causal signal interpretation.

Same stage of the pathData-Driven Management and Decision Operating System9 lessons

Bring data into the everyday way of deciding with cadence, governance, decision memo, and cross-functional alignment.

Next moduleProduct Analytics and Growth Diagnostics11 lessons

Read where the product creates value, friction, or loss with funnel, retention, activation, and monetization analytics.

Next moduleMarketing Analytics, Incrementality, and Unit Economics22 lessons

Take marketing from reporting to a serious quantitative discipline with incrementality, unit economics, and decision reviews.

Next moduleDashboard, Visualization, and Decision Interface8 lessons

Build dashboards that drive decisions, with visual hierarchy, semantic consistency, alerting, and operational context.