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Time Series Analysis and Forecasting with Python

Time Series Analysis and Forecasting with Python

Learn Python for Pandas, Statsmodels, ARIMA, SARIMAX, Deep Learning, LSTM, and Forecasting into Future

What you’ll learn

Time Series Analysis and Forecasting with Python

  • Basic Packages, NumPy, Pandas & Matplotlib

  • Time Series with Pandas (Creating Date Time index, Resampling, …)

  • Analyzing Time Series Data Using Statsmodels Package

  • The Concept of ARIMA and SARIMAX method and How to Forecast into the Future Using Them

  • The Concept of Deep Learning from A-Z

  • Forecast into the Future Using LSTM Model for Single Variant

  • Forecast into the Future Using LSTM Model for Multi Variant


  • General and Basic Python Skills


The “Time Series Analysis and Forecasting with Python” Course is the ultimate source for learning the concepts of Time Series and forecast into the future.

In this course, the most famous methods such as statistical methods (ARIMA and SARIMAX) and Deep Learning Methods (LSTM) are explained in detail. Furthermore, several Real World projects are developed in a Python environment and have been explained line by line!

If you are a researcher, a student, a programmer, or a data science enthusiast that is seeking a course that shows you all about time series and prediction from A-Z, you are in the right place.

Just check out what you will learn in this course below:

  • Basic libraries (NumPy, Pandas, Matplotlib)
  • How to use Pandas library to create DateTime index and how to set that as your Dataset index
  • What are statistical models?
  • How to forecast into future using the ARIMA model?
  • Learn how to capture the seasonality using the SARIMAX model?
  • How to use endogenous variables and predict into future?
  • What is Deep Learning (Very Basic Concepts)
  • All about Artificial and Recurrent Neural Networks!
  • How the LSTM method Works!
  • Learn how to develop an LSTM model with a single variate.
  • How to develop an LSTM model using multiple variables (Multivariate)

As I mentioned above, in this course we tried to explain how you can develop an LSTM model when you have several predictors (variables) for the first time and you can use that for several applications and use the source code for your project as well!

This course is for Everyone! yes everyone! that wants t to learn time series and forecasting into the future using statistics and artificial intelligence with any kind of background! Even if you are not a programmer, I show you how to code and develop your model line by line!

If you want to master the basics of Machine Learning in Python as well, you can check out my other courses!

Who this course is for:

  • Data Science Enthusiast
  • Beginner Programmers
  • Python Developers
  • Researchers who like to forecast into future
  • Data Analysts
  • Anyone who is interested in Time Series and Future Forecasting

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