Course details

Predictive Modelling Best Practices: Applying Predictive Analytics

Predictive Modelling Best Practices: Applying Predictive Analytics


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Discover the predictive modeling process and how to apply tools and techniques for performing predictive analytics.



Expected Duration (hours)
1.5

Lesson Objectives

Predictive Modelling Best Practices: Applying Predictive Analytics

  • describe predictive analytics is and where it is applicable
  • recognize the predictive modeling process, including how to explore and understand data, prepare for and model data, and evaluate and deploy the model
  • identify methods for random sampling and use hypothesis testing, Chi-square tests, and correlation
  • recognize common model categories and analytical techniques
  • use Decision Trees and Support Vector Machines for predictive analytics
  • use Survival Analysis to predict and analyze customer churn
  • use Market Basket Analysis to perform predictive analysis
  • apply data clustering models to perform predictive analysis
  • apply random forests for predictive analytics
  • use Naive Bayes classifiers for predictive analytics
  • use Logistic Regression for predictive analytics
  • describe best practices in predictive modeling
  • apply models to perform predictive analytics
  • Course Number:
    it_mlpmbpdj_01_enus

    Expertise Level
    Beginner