Time Series Forecasting in R: A Down-to-Earth Approach
Published 10/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 81 lectures (8h 3m) | Size: 3.41 GB
High-performance forecasting tools made easy to understand and apply
What you'll learn
Know the time series forecasting steps
Know the essential time series components
Know the most important forecasting accuracy metrics
Use the moving averages and the simple exponential smoothing techniques
Use the advanced exponential smoothing techniques: Holt and Holt-Winters
Use extended exponential smoothing models: TBATS and STLM
Build regression models with trend only
Build regression models with trend and seasonality
Understand important concepts like autocorrelation, stationarity and integration
Use the augmented Dickey-Fuller test for stationarity
Build autoregressive integrated moving average models (ARIMA)
Build neural networks for time series forecasting
Requirements
Basic R programming notions
Basic statistics notions
Description
Become the Best Time Series Expert in Your Organisation!
The goal of this course is to convert you into a highly-skilled time series forecaster. You will learn the most effective forecasting techniques that analysts use every day to make accurate predictions about the future. This will make you invaluable for your organisation and help you speed up your career like a flash. A time series analyst makes about $70,000 a year on average, but the top performers can make as much as $130,000 (according to SimplyHired).
This course will be a revolution for you, even if you don't know anything about time series forecasting at this point. After completing it you will know how to...
investigate historical data,
detect trends and patterns
choose the most appropriate forecasting methods
assess forecasting...
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