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“Time Series Analysis and Forecasting with Python” Course is an 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 Method (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 a 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?
- 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 Network!
- How the LSTM method Works!
- 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 my other courses!