Time Series Analysis and Forecasting using Python
Learn about time series analysis & forecasting models in Python |Time Data Visualization |AR|MA |ARIMA |Regression | ANN
4.52 (1799 reviews)

159 896
students
13.5 hours
content
May 2025
last update
$79.99
regular price
What you will learn
Get a solid understanding of Time Series Analysis and Forecasting
Understand the business scenarios where Time Series Analysis is applicable
Building 5 different Time Series Forecasting Models in Python
Learn about Auto regression and Moving average Models
Learn about ARIMA and SARIMA models for forecasting
Use Pandas DataFrames to manipulate Time Series data and make statistical computations
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Our Verdict
Time Series Analysis and Forecasting using Python is a well-structured course that covers essential methods from both theoretical and practical perspectives. However, be prepared to encounter occasional inconsistencies in lecture order and some outdated information, requiring extra effort for clarification from the community Q&A section. If you are new to time series analysis but have a strong grasp of Python programming, this course will serve as an informative starting point that lays a solid foundation for further advanced studies.
What We Liked
- Comprehensive coverage of time series analysis and forecasting methods, including AR, MA, ARIMA, SARIMA, regression, and artificial neural networks
- Practical data manipulation using Pandas DataFrames for time series data
- Clear video explanations and real-world examples
- Highly subscribed course with an impressive 4.52 global rating
Potential Drawbacks
- Occasional use of deprecated Python functions and lack of some important concepts, such as stationarity
- Inconsistent lecture order that can make the learning experience less coherent
- Limited predictive modeling on time series data in certain sections
- Insufficient practice datasets and assignments for more hands-on experience
Related Topics
2859872
udemy ID
09/03/2020
course created date
21/03/2020
course indexed date
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