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)
Udemy
platform
English
language
Data Science
category
Time Series Analysis and Forecasting using Python
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

Course Gallery

Time Series Analysis and Forecasting using Python – Screenshot 1
Screenshot 1Time Series Analysis and Forecasting using Python
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Screenshot 2Time Series Analysis and Forecasting using Python
Time Series Analysis and Forecasting using Python – Screenshot 3
Screenshot 3Time Series Analysis and Forecasting using Python
Time Series Analysis and Forecasting using Python – Screenshot 4
Screenshot 4Time Series Analysis and Forecasting using Python

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Comidoc Review

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 However, be prepared to encounter occasional inconsistencies in lecture order and some outdated information, requiring extra effort for clarification from the community Q&A section.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
Bot
course submited by
Time Series Analysis and Forecasting using Python - Coupon | Comidoc