Forecasting Course
This course equips you with practical skills to create accurate and explainable time series forecasts for e-commerce, covering data preparation, classical and ML models, evaluation, and communication.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Forecasting Course gives you practical, end-to-end skills to build accurate, explainable time series forecasts for e-commerce. Learn data preparation, feature engineering, and exploratory analysis, then master ARIMA, SARIMA, exponential smoothing, and ML-based models. You will practice backtesting, error metrics, scenario planning, and clear communication so your forecasts drive confident, data-informed decisions.
Elevify advantages
Develop skills
- Clean time series data: fix outliers, gaps, and timestamps for BI-ready forecasts.
- Build and tune ARIMA, SARIMA, and exponential smoothing models in real cases.
- Evaluate forecast accuracy with MAE, RMSE, MAPE and clear business meaning.
- Use drivers like marketing spend and promos for causal, scenario-based forecasts.
- Present forecasts with visuals, scenarios, and actions for e-commerce decisions.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workloadWhat our students say
Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change platforms... I thank you for everything you do, I've already recommended you to other people...

Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.

Mariana FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.

André FelipePrompt Engineering Student
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