Ementorhub

Predictive Modeling, Model Fitting, and Regression Analysis

This course is part of Data Science Fundamentals Specialization

Instructor: Julie Pai

What you'll learn

The application of predictive modeling to professional and academic work

Applications of classification analysis: decision trees

Applications of regression analysis (linear and logistic)

Skills you'll gain

Unsupervised Learning

Predictive Analytics

Forecasting

Machine Learning

Statistical Modeling

Descriptive Analytics

Data Modeling

Regression Analysis

Predictive Modeling

Statistical Analysis

Decision Tree Learning

Supervised Learning

Classification And Regression Tree (CART)

Data Analysis

There are 4 modules in this course

Welcome to Predictive Modeling, Model Fitting, and Regression Analysis. In this course, we will explore different approaches in predictive modeling, and discuss how a model can be either supervised or unsupervised. We will review how a model can be fitted, trained and scored to apply to both historical and future data in an effort to address business objectives. Finally, this course includes a hands-on activity to develop a linear regression model.

Data Dimensionality and Classification Analysis

Model Fitting

Regression Analysis

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