Time Series Analysis with Python
Beginner
38 Lessons
10h
Certificate of Completion
Takeaway Skills
An understanding of time series data analysis concepts, such as stationarity, autocorrelation and seasonality
Working knowledge of Python libraries for time series data analysis, such as Pandas and NumPy
Hands-on experience analyzing and forecasting time series data using Python
Ability to use statistical modeling techniques, such as ARIMA, to forecast time series data
Familiarity with advanced techniques for time series data analysis, such as machine learning algorithms and neural networks
Course Overview
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 l...Show More
Course Content
Introduction to Time Series
Python Basics for Time Series
Time Series Analysis
Basic Time Series Forecasting
Advanced Time Series Forecasting
Forecast Evaluation
5 Lessons
Time Series Analysis and Forecasting
Assessment
Practical Examples
3 Lessons
Final Project
Project
Conclusion
1 Lesson
How You'll Learn
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