Intermediate
40 Lessons
7h
Certificate of Completion
AI-POWERED
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This course includes
This course includes
Course Overview
Time series are all around us, from stock prices and weather forecasts to economic trends and medical diagnoses. This course is designed to equip you to effectively model, interpret, and forecast time series. In this course, you’ll learn time series analysis concepts, such as stochasticity, stationarity, and autocorrelation. You’ll analyze the time series by computing its various moments and by visualizing it using histogram and density plots. Next, you’ll decompose the time series into its trend, season, ...
What You'll Learn
Understanding of properties of time series, including its moments, stationarity, autocorrelation, seasonality, and trend
Hands-on experience in analyzing and modeling real-world time series using Python’s statsmodel
Familiarity with modeling time series as autoregressive (AR) and moving average (MA) processes and their combinations ARMA and ARIMA
Working knowledge of point forecasting with ARIMA models using Pythons’s statsmodel
What You'll Learn
Understanding of properties of time series, including its moments, stationarity, autocorrelation, seasonality, and trend
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Course Content
Introduction to Time Series
The Basics of Time Series
Exploring Data
The Properties of Time Series
ARIMA Models
On Prediction
4 Lessons
Choosing, Fitting, and Evaluating Models
6 Lessons
Conclusion
1 Lesson
Appendix
2 Lessons
What have you learned?
Assessment
Course Author
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Anthony Walker
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Emma Bostian 🐞
@EmmaBostian
Evan Dunbar
ML Engineer
Carlos Matias La Borde
Software Developer
Souvik Kundu
Front-end Developer
Vinay Krishnaiah
Software Developer
Eric Downs
Musician/Entrepeneur
Kenan Eyvazov
DevOps Engineer
Anthony Walker
@_webarchitect_
Emma Bostian 🐞
@EmmaBostian
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