Time Series in Python

Uppdaterad 2026-03

Gain the skills you need to manipulate, interpret, and visualize time series data in Python, using pandas, NumPy, and Matplotlib.

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Spårbeskrivning

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.

Förkunskapskrav

Det finns inga förkunskapskrav för detta spår

Course
1
Manipulating Time Series Data in Python
In this course you'll learn the basics of working with time series data.
Course
2
Time Series Analysis in Python
In this four-hour course, you’ll learn the basics of analyzing time series data in Python.
Course
3
Visualizing Time Series Data in Python
Visualize seasonality, trends and other patterns in your time series data.
Course
4
ARIMA Models in Python
Learn about ARIMA models in Python and become an expert in time series analysis.
Project
Bonus
Time Series Analysis for Transportation
Explore transportation time series data analysis to uncover patterns and forecast travel costs.
Course
6
Machine Learning for Time Series Data in Python
This course focuses on feature engineering and machine learning for time series data.

Time Series in Python

5 courses

Spår
klart

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Genom att fortsätta accepterar du våra Användarvillkor, vår Integritetspolicy och att dina uppgifter lagras i USA.

Spårbeskrivning

Time Series in Python

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Gå med över 19 miljoner elever och börja Time Series in Python idag!