Time Series Analysis and Forecasting using Python

Learn about time series analysis & forecasting models in Python |Time Data Visualization |AR|MA |ARIMA |Regression | ANN

4.50 (1812 reviews)

Udemy

platform

English

language

Data Science

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

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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 However, be prepared to encounter occasional inconsistencies in lecture order and some outdated information, requiring extra effort for clarification from the community Q&A section.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