Time Series Modeling in Excel, R, and Power BI
Time Series Modeling in Excel, R, and Power BI
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h | 412 MB
Instructor: Helen Wall
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h | 412 MB
Instructor: Helen Wall
The use of time series models has become a central topic in today’s data science world. In this course, instructor Helen Wall shows you how to run autoregressive integrated moving average (ARIMA) models as predictive, time series modeling tools in Excel, R, and Power BI.
Explore the building blocks of a time series decomposition, which lets you make data forecasts with accuracy, consistency, and ease. Take a deep dive into the fundamentals of autoregressive coefficients, autocorrelation, moving average coefficients, stationarity and random walks with integrated components, and how to forecast time series models using Power BI. By the end of this course, you’ll be ready to start wielding your new data analytics skills to make more timely and effective decisions for your business.
Time Series Modeling in Excel, R, and Power BI
