Mastering Time Series Forecasting with Python

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Mastering Time Series Forecasting with Python

About this course

Welcome to Mastering Time Series Forecasting in PythonTime series analysis and forecasting is one of the areas of Data Science and has a wide variety of applications in the industries in the current world. Many industries looking for a Data Scientist with these skills. This course covers all types of modeling techniques for forecasting and analysis. We start with programming in Python which is the essential skill required and then we will exploring the fundamental time series theory to help you understand the modeling that comes afterward.Then throughout the course, we will work with a number of Python libraries, providing you with complete training. We will use the powerful time-series functionality built into pandas, as well as other fundamental libraries such as NumPy, matplotlib, statsmodels, Sklearn, and ARCH.With these tools we will master the most widely used models out there:Additive ModelMultiplicative ModelAR (autoregressive model)Simple Moving AverageWeighted Moving AverageExponential Moving AverageARMA (autoregressive-moving-average model)ARIMA (autoregressive integrated moving average model)Auto ARIMAWe know that time series is one of those topics that always leaves some doubts.Until now.This course is exactly what you need to comprehend the time series once and for all. Not only that, but you will also get a ton of additional materials – notebooks files, course notes – everything is included.

What you'll learn

  • understand time series theory
  • use pandas for time-series functionality
  • implement various forecasting models including ARIMA and moving averages
  • apply different Python libraries like NumPy and matplotlib

Skills you'll gain

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