Medical Insurance Premium Prediction with Machine Learning

Offered By
Coursera Project Network
In this Guided Project, you will:

Understand the theory and intuition behind artificial neural networks

Build, train and test an artificial neural network model in Keras and Tensorflow

Perform data cleaning, feature engineering and visualization

Clock2 hours
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 1-hour long project-based course, you will learn how to predict medical insurance cost with machine learning. The objective of this case study is to predict the health insurance cost incurred by Individuals based on their age, gender, Body Mass Index (BMI), number of children, smoking habits, and geo-location. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

  • Data Science
  • Artificial Neural Network
  • Python Programming
  • Machine Learning

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Understand the Problem Statement

  2. Import Libraries and Datasets

  3. Perform Exploratory Data Analysis

  4. Practice Opportunity #1 [Optional]

  5. Perform Feature Engineering

  6. Perform Data Visualization

  7. Practice Opportunity #2 [Optional]

  8. Create Training and Testing Datasets

  9. Practice Opportunity #3 [Optional]

  10. Train and Evaluate a Linear Regression Model in Sk-Learn

  11. Train and Evaluate an Artificial Neural Network Regression Model

  12. Practice Opportunity #4 [Optional]

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.