Time Series Forecasting in R: A Down-to-Earth Approach

High-performance forecasting tools made easy to understand and apply
4.64 (32 reviews)
Udemy
platform
English
language
Data & Analytics
category
Bogdan Anastasiei
instructor
Time Series Forecasting in R: A Down-to-Earth Approach
315
students
8 hours
content
Oct 2022
last update
$69.99
regular price

What you will 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

Screenshots

Time Series Forecasting in R: A Down-to-Earth Approach - Screenshot_01Time Series Forecasting in R: A Down-to-Earth Approach - Screenshot_02Time Series Forecasting in R: A Down-to-Earth Approach - Screenshot_03Time Series Forecasting in R: A Down-to-Earth Approach - Screenshot_04
Related Topics
4904116
udemy ID
9/28/2022
course created date
10/28/2022
course indexed date
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course submited by
Time Series Forecasting in R: A Down-to-Earth Approach - Coupon | Comidoc