Time Series Analysis in Python
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In this four-hour course, you’ll learn the basics of analyzing time series data in Python.
Course Description
Learn How to Use Python for Time Series Analysis
From stock prices to climate data, you can find time series data in a wide variety of domains. Having the skills to work with such data effectively is an increasingly important skill for data scientists. This course will introduce you to time series analysis in Python.
After learning what a time series is, you’ll explore several time series models, ranging from autoregressive and moving average models to cointegration models. Along the way, you’ll learn how to estimate, forecast, and simulate these models using statistical libraries in Python.
You’ll see numerous examples of how these models are used, with a particular emphasis on applications in finance.
Discover How to Use Time Series Methods
You’ll start by covering the fundamentals of time series data, as well as simple linear regression. You’ll cover concepts of correlation and autocorrelation and how they apply to time series data before exploring some simple time series models, such as white noise and a random walk.
What You’ll Learn
Correlation and Autocorrelation
In this chapter you’ll be introduced to the ideas of correlation and autocorrelation for time series. Correlation describes the relationship between two time series and autocorrelation describes the relationship of a time series with its past values.
Autoregressive (AR) Models
In this chapter you’ll learn about autoregressive, or AR, models for time series. These models use past values of the series to predict the current value.
Putting It All Together
This chapter will show you how to model two series jointly using cointegration models. Then you’ll wrap up with a case study where you look at a time series of temperature data from New York City.
Some Simple Time Series
In this chapter you’ll learn about some simple time series models. These include white noise and a random walk.
Moving Average (MA) and ARMA Models
In this chapter you’ll learn about another kind of model, the moving average, or MA, model. You will also see how to combine AR and MA models into a powerful ARMA model.
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