Course overview

In this course, you’ll go through each step of a typical data science project: data cleaning, preparing the features and feature selection, and making predictions. You’ll use loan data from the Lending Club to try to solve a real-world business problem for any lender: predicting loan payoffs.

In order to predict a loan payoff, you will train, test, and iterate to improve the following machine learning models: logistic regression, neural networks, decision trees, and the random forest algorithm. You’ll also learn how to choose an appropriate error metric for your model.

At the end of the course, you’ll complete a realistic, end-to-end data science project, and you will have worked through the entire data science life cycle. This project is a chance for you to combine the skills you have learned so far, and it also serves as a portfolio project that you can show to future employers to demonstrate your skills across a complete data science project.

Key skills

    • Completing a machine learning project from start to finish

Course outline

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Projects in this course

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Build your project portfolio

Build confidence with our in-depth projects, and show off your data skills.

Challenge yourself with exercises

Work with real data from day one with interactive lessons and hands-on exercises.

Showcase your course certification

Impress employers by completing a capstone project and certifying it with an expert review.

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