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Mining Data from Time Series

by Martin Burger

Master time series analysis in Python and be able to produce powerful quantitative forecasts.

What you'll learn

Are you struggling with the analysis of time series data or do you want to create a powerful quantitative forecasting model in Python? In this course, Mining Data from Time Series, you will gain the ability to model and forecast time series in Python. First, you will learn about time series data, which is data captured along a timeline with specific statistical traits crucial for any model. Then, you will see the statistical foundations first before diving into the classic time series models of ARIMA, seasonal decomposition as well as exponential smoothing. Finally, you will explore some advanced concepts like the new Prophet package from Facebook or multivariate time series. When you are finished with this course, you will have the skills and knowledge of time series analysis needed to model and forecast standard univariate time series data sets.

About the author

Martin studied biostatistics and worked for several pharmaceutical companies before he became a data science consultant and author. He published over 15 courses on R, Tableau 9 and other data science related subjects. His main focus lies on analytics software like R and SPSS but he is also interested in modern data visualization tools like Tableau. If he is not busy coding, blogging or working out new teaching concepts you may find him skiing or hiking in the Alps.

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