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Time Series Forecasting with Python: Models to Production

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Board Infinity

Time Series Forecasting with Python: Models to Production

Board Infinity

Instructor: Board Infinity

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Build and evaluate statistical models: exponential smoothing, Holt-Winters, ARIMA, SARIMA, SARIMAX, and Prophet.

  • Implement deep learning architectures: LSTM, GRU, CNN-LSTM hybrids, and Temporal Fusion Transformers.

  • Frame forecasting as supervised learning and train tree-based models with leak-free time series cross-validation.

Details to know

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Recently updated!

June 2026

Assessments

16 assignments

Taught in English

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There are 4 modules in this course

Learn the fundamentals of time series data and how to prepare it for modeling.

What's included

12 videos4 assignments

Explore traditional statistical methods for forecasting time series.

What's included

12 videos4 assignments

Learn how to apply modern ML and DL techniques to time series data.

What's included

12 videos4 assignments

Learn how to handle multiple time series, ensemble models, and deploy them to production.

What's included

12 videos2 readings4 assignments

Instructor

Board Infinity
Board Infinity
264 Courses434,320 learners

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