Course details

Predictive Analytics & Big Data

Predictive Analytics & Big Data


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



Overview/Description
Predictive analytics uses techniques, such as statistics and machine learning, to build predictive models, often using big data to test and validate these models. Explore key features of predictive analytics and big data.

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)
0.7

Lesson Objectives

Predictive Analytics & Big Data

  • start the course
  • recognize what predictive analytics is, the types of models used, and what its goals are
  • recognize what types of questions are answered by predictive analytics and who uses it
  • identify key features of predictive analytics
  • recognize key features of big data
  • recognize the considerations of using big data and what the sources are
  • identify key features of time series, uplift, and logistic models
  • identify key features of classification trees, neural networks, support vector machines, and Bayesian networks
  • recognize key differences between predictive analytics and traditional business intelligence
  • Course Number:
    df_prma_a01_it_enus

    Expertise Level
    Intermediate