Time Series Forecasting Course
This course offers a practical guide to time series forecasting, covering data preparation, model building with ARIMA, Prophet, and ML techniques, evaluation, and deployment for real-world applications like sales forecasting.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Time Series Forecasting Course provides a quick, hands-on route from raw daily sales data to dependable, production-ready forecasts. You will clean and validate data, create strong calendar and event features, use ARIMA, exponential smoothing, Prophet, and modern ML models, adjust and assess them with solid backtesting, and ultimately deploy, monitor, and share forecasts that support improved planning choices.
Elevify advantages
Develop skills
- Clean time series data: ingest, validate, and impute daily sales quickly.
- Build solid ARIMA, SARIMA, and ETS baselines with proper diagnostics.
- Engineer calendar, lag, and promo features that improve forecast accuracy.
- Apply ML forecasters like Prophet and gradient boosting to sales series.
- Evaluate, deploy, and monitor forecasts that guide inventory 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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