Course details

Time Series Modeling

Time Series Modeling


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description
Time series modeling is a common forecasting method, such as making stock market predictions. It has made its way into many varied applications, including inventory management and healthcare. Explore the features of time series modeling.

Target Audience
All individuals who are new to predictive analytics and wish to use it to optimize their business performance; business leaders; analysts; marketing, sales, software, and IT professionals who want to add predictive analytics to their skill set; and decision makers of any kind

Prerequisites
None

Expected Duration (hours)
0.6

Lesson Objectives

Time Series Modeling

  • start the course
  • identify key characteristics of time series forecasting
  • distinguish between stationary time series and nonstationary time series data
  • recognize the various components of time series data
  • identify features of autoregressive models
  • identify features of moving average models
  • identify features of ARMA models
  • identify various steps required to make a forecast
  • apply time series modeling concepts
  • Course Number:
    df_prma_a14_it_enus

    Expertise Level
    Intermediate