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.
This course is part of the Data Science Fundamentals Specialization
Offered By


About this Course
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
The application of predictive modeling to professional and academic work
Applications of classification analysis: decision trees
Applications of regression analysis (linear and logistic)
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Predictive Modeling
Data Dimensionality and Classification Analysis
Model Fitting
Regression Analysis
Reviews
- 5 stars67.34%
- 4 stars16.32%
- 3 stars8.16%
- 2 stars4.08%
- 1 star4.08%
TOP REVIEWS FROM PREDICTIVE MODELING, MODEL FITTING, AND REGRESSION ANALYSIS
Thank you Very Much I learn a lot of Thing with all kinds of Predative Modeling that I can use.
course content is very concise and easy to understand
good course to understand the fundamentals of predictive analysis
About the Data Science Fundamentals Specialization

Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I subscribe to this Specialization?
Is financial aid available?
More questions? Visit the Learner Help Center.