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Time Series in Python

Time series data is one of the most common data types and understanding how to work with it is a critical data science skill if you want to make predictions and report on trends. In this track, you'll learn how to manipulate time series data using pandas, work with statistical libraries including NumPy and statsmodels to analyze data, and develop your visualization skills using Matplotlib, SciPy, and seaborn. You'll then apply your time series skills using real-world data, including financial stock data, UFO sightings, CO2 levels in Maui, monthly candy production in the US, and heartbeat sounds. By the end of this track, you'll know how to forecast the future using ARIMA class models and generate predictions and insights using machine learning models.

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1
Manipulating Time Series Data in Python

In this course you'll learn the basics of working with time series data.

4 hours

Stefan Jansen Headshot

Stefan Jansen

Founder & Lead Data Scientist at Applied Artificial Intelligence

2
Time Series Analysis in Python

In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

4 hours

Rob Reider Headshot

Rob Reider

Consultant at Quantopian and Adjunct Professor at NYU

3
Visualizing Time Series Data in Python

Visualize seasonality, trends and other patterns in your time series data.

4 hours

Thomas Vincent Headshot

Thomas Vincent

Head of Data Science at Getty Images

4
ARIMA Models in Python

Learn about ARIMA models in Python and become an expert in time series analysis.

4 hours

James Fulton Headshot

James Fulton

Climate Informatics Researcher

5
Machine Learning for Time Series Data in Python

This course focuses on feature engineering and machine learning for time series data.

4 hours

Chris Holdgraf Headshot

Chris Holdgraf

Fellow at the Berkeley Institute for Data Science

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