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