Time Series Forecasting Course
Master daily sales forecasting from raw data to production-ready models. Learn cleaning, feature engineering, ARIMA, Prophet, and ML methods, then turn accurate, interpretable forecasts into better inventory, staffing, and promotion decisions.

flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
This Time Series Forecasting Course gives you a fast, practical path from raw daily sales data to reliable, production-ready forecasts. You will clean and validate data, engineer powerful calendar and event features, apply ARIMA, exponential smoothing, Prophet, and modern ML models, tune and evaluate them with robust backtesting, and finally deploy, monitor, and communicate forecasts that drive better planning decisions.
Elevify advantages
Develop skills
- Clean time series data: ingest, validate, and impute daily sales fast.
- Build robust ARIMA, SARIMA, and ETS baselines with sound diagnostics.
- Engineer calendar, lag, and promo features that boost forecast accuracy.
- Apply ML forecasters like Prophet and gradient boosting to sales series.
- Evaluate, deploy, and monitor forecasts that drive inventory decisions.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workloadWhat our students say
Your classes are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...

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

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

Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the extra videos really help with learning.

Giulio CarloPrompt Engineering Student
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