DLSEI 3.0 Cohort 3 registration has been closed.

Predict Employee Turnover with scikit-learn

Included with DLSEI 3.0

Guided Project

Learn, practice, and apply job-ready skills with expert guidance

4.42★

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Guided project Level

Recommended experience

1.00 Hours

Learn at your own pace

Data Science

Domain

About this guided project

Welcome to this project-based course on Predicting Employee Turnover with Decision Trees and Random Forests using scikit-learn. In this project, you will use Python and scikit-learn to grow decision trees and random forests, and apply them to an important business problem. Additionally, you will learn to interpret decision trees and random forest models using feature importance plots. Leverage Jupyter widgets to build interactive controls, you can change the parameters of the models on the fly with graphical controls, and see the results in real time! This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed.

What skills will you gain?

Applied Machine Learning

Machine Learning

Machine Learning Methods

Data Science

Predictive Modeling

Predictive Analytics

Statistical Machine Learning

Supervised Learning

Machine Learning Algorithms

Statistical Modeling

Artificial Intelligence and Machine Learning (AI/ML)

Random Forest Algorithm