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Time Series Analysis with Python

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level

Beginner

Duration

10h

Lessons

38 Lessons

Gain the ability to analyze and visualize time series data using Python.

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This course is an introduction to time series data analysis and forecasting with Python. Time series data is prevalent in many fields, including finance, economics, and meteorology. In this course, you will learn how to use Python’s popular pandas and NumPy libraries to manipulate, visualize, and analyze time series data.

The course covers topics such as time series decomposition, stationary and non-stationary data, autocorrelation and partial autocorrelation, and modeling techniques like ARIMA. You will learn how to implement these techniques in Python and how to use them to make forecasts. Moreover, you will also be introduced to some advanced techniques including machine learning algorithms.

By the end of the course, you will have a solid understanding of time series data analysis and forecasting with Python. You will be able to import, clean, and manipulate time series data, use statistical modeling techniques to make forecasts, and apply machine learning algorithms to time series data.

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Time Series Analysis with Python
Time Series Analysis with Python
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