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Predictive Modeling: Predictive Analytics & Exploratory Data Analysis

Predictive Modeling: Predictive Analytics & Exploratory Data Analysis


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Explore the predictive analytics, exploratory data analytics, and different types of datasets and variables. Discover how to implement predictive models and manage missing values and outliers using Python frameworks.



Expected Duration (hours)
0.7

Lesson Objectives

Predictive Modeling: Predictive Analytics & Exploratory Data Analysis

  • define the predictive analytics and describe its process flow
  • describe analytical base table and how it can be used to build and score analytical models
  • identify the business problems that can be resolved using predictive modeling
  • build predictive models using the Python framework
  • list essential features of exploratory data analysis
  • describe univariate, bivariate, and multivariate data and analytical approaches that can be implemented with them
  • specify methods that can be used to manage missing values and outliers in datasets
  • list applications of predictive analytics, describe analytical base tables, list predictive models, and specify variable selection methods
  • Course Number:
    it_mlfupddj_01_enus

    Expertise Level
    Intermediate