MODULE 1
Marketing questions
objectives, forecast horizon, available variables and outcome definitions.
Vibecoding
Vibe Coding and Predictive Marketing: Forecast Sales and Customer Behavior
The Vibe Coding and Predictive Marketing course covers applications for forecasting, customer scoring and predictive segmentation. Learn to organize data and evaluation to explore sales, conversions and customer behavior without treating estimates as certainties.
Understand. Apply. Evaluate.
Proposed duration12 hours
Programme6 course modules
ArrangementsInformation on request
Why choose this course.
A forecast is useful when its horizon, error and supported decision are clear. The course connects these elements to building a demonstration application.
THE SKILLS
What you will learn.
- Define a predictive question linked to a marketing decision.
- Evaluate a forecast against a baseline and held-out data.
- Present scores and segments with explicit limitations and criteria.
- Design an interface that distinguishes observations from estimates.
THE PROGRAMME
A course, step by step.
MODULE 2
Data preparation
history, quality, temporal separation and leakage prevention.
MODULE 3
Forecasting
baselines, sales estimates and error comparisons on periods not used in development.
MODULE 4
Customer scoring and segments
criteria, probabilities, thresholds and group interpretation.
MODULE 5
Conversions and scenarios
comparisons, visualizing estimates and communicating uncertainty.
MODULE 6
Application testing
metrics, data checks, recommendation reviews and monitoring.
What the course includes
- Applied exercise described in the programme
WHO IT IS FOR
Find your starting point.
- Marketing analysts and CRM leads
- Sales managers and business analysts
- Consultants and professionals with data analysis foundations
Before you start
- Basic knowledge of marketing KPIs, data and descriptive statistics.
- Spreadsheet foundations; Python or SQL helps with more detailed checks.
References and further reading
An example application
Build an application using demonstration sales and customer data: compare a forecast with a baseline, explore segments and summarize errors, data used and recommendation limitations.
YOUR QUESTIONS, ANSWERED
Questions about the course.
Do predictions establish what customers will certainly do?
No. They are estimates subject to error and changing conditions. The programme requires error measurement and review before decisions.
Why separate data over time?
To evaluate estimates on information not used in development and reduce artificially optimistic results. The appropriate split depends on the problem and data.
What is the proposed duration?
The proposed duration is 12 hours. The school will confirm scheduling, session structure, delivery arrangements and tool requirements according to the agreed course.
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Programme and detailsYOUR NEXT STEPYour next step
Your next step
starts here.
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