Predictive Analytics & Big Data

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

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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)
0.6

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