An Introduction to Time Series

Intermediate

40 Lessons

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

1 Assessment

82 Playgrounds

6 Quizzes

This course includes

1 Assessment

82 Playgrounds

6 Quizzes

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, ...Show More

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

Course Content

Introduction to Time Series

About This Course

Course Structure

The Basics of Time Series

Stochastic Processes Recurrence and Stationarity Some Basic Examples of Time Series Our Use Case Quiz

Exploring Data

Moments of a Time Series: Mean and Variance Moments of a Time Series: Skewness and Kurtosis Histograms and Density Plots Normality, the Q-Q Plot and the Jarque-Bera Test Quiz

The Properties of Time Series

Integration A Note on Stocks vs. Returns The Dickey-Fuller Test The KPSS and Phillips-Perron Tests Autocorrelation Partial Autocorrelation Testing for Autocorrelation Trends, Seasons, and Cycles Filters Quiz

ARIMA Models

Moving Average Processes (MA)Autoregressive Processes (AR)ARMA and ARIMA Processes Seasonal ARIMA Quiz

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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Emma Bostian 🐞

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