What can be done with thousands of online store purchase records? How can we analyze this data and predict its growth? In this course, you will learn what parameters we can analyze in time series and how to create predictive models. Let's get started!

Start from the introduction to time series to move on to more in-depth topics. Find out what it is, how often time series occur in real business, how to analyze them and make forecasts.

What is the difference between trend and seasonality? Is the data I'm working with stationary or not? In this section, you will learn how to analyze characteristics of time series using Python!


Learn more about time series through… their visualization! Explore your data with 2D and 3D graphs.


What will be our first step? Let's start with stationary models! Create your first predictive model that will forecast time series.

Most of the data you work with is non-stationary. Learn how to process such data and what models to use to predict it.

Let's dive into a variety of interesting tasks that you may encounter while working with time series! Find out how big these challenges are and what models we can use to solve them.

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