Data Preprocessing


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



Overview/Description
Predictive analytics delivers the greatest value when the data being modeled is relevant to the business goals. Explore the preprocessing phase of data collection to provide the best predictive model.

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)
0.5

Lesson Objectives

Data Preprocessing

  • start the course
  • recognize what is tidy and what is untidy data
  • identify outliers and determine whether to remove these values
  • perform data transformation, normalization, and scaling
  • recognize important aspects of variable partitioning
  • recognize important aspects of setting dummy variables and removing variables
  • recognize key approaches for handling missing data
  • use imputation to replace missing data
  • Course Number:
    df_prma_a07_it_enus

    Expertise Level
    Intermediate