Dong

“I liked Dataquest because I can control how fast I do the problems. The small scale projects help to make the transition from concepts to the real thing. I wished I had found it earlier.”

Dong Zhou

Senior Scientist @Schrödinger

Course overview

Decision trees are known in the machine learning world for a particularly distinctive characteristic: their visualizations are easier to understand compared to other machine learning models, and for this reason, they are very suitable for explaining insights to non-technical audiences.

In this course, you’ll learn the foundations of Decision Trees including identifying the key components of trees, interpreting them, classifying new observations using decision trees and calculating optimal thresholds for both classification and regression trees. You’ll also learn how to build and visualize decision trees by adapting a real-life dataset to train tree models, selecting the appropriate scikit-learn tools to build your model, and training, testing and visualizing decision trees.

You’ll be able to evaluate and optimize trees for better performance including activities such as establishing the optimal depth for a decision tree, using Prune decision trees to avoid overfitting, or manipulating sample distribution in nodes and leaves.

Finally, you’ll learn how to apply the cross validation and ensemble techniques for decision trees. You’ll identify the differences between decision trees and random forest models, develop and customize random forest models and optimize the parameters of random forest.

Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser. At the end of the course, you’ll combine your new skills in a project to predict employee productivity with tree models

Key skills

  • Creating, customizing, and visualizing Decision Trees
  • Using and interpreting Decision Trees on new data
  • Optimizing trees by altering their parameters
  • Applying the Random Forest prediction technique

Course outline

Decision Tree and Random Forest Modeling in Python [5 lessons]

Foundations of Decision Trees 2h

Lesson Objectives
  • Identify key components of trees
  • Interpret decision trees
  • Classify new observations using decision trees
  • Calculate optimal thresholds for both classification and regression trees

Building Decision Trees Using Scikit-learn 2h

Lesson Objectives
  • Adapt a real-life dataset to train tree models
  • Select the appropriate scikit-learn tools to build decision trees
  • Train and test decision trees
  • Visualize decision trees

Evaluating and Optimizing Decision Trees 2h

Lesson Objectives
  • Evaluate the trees' performance
  • Optimize your trees
  • Establish the optimal depth for a decision tree
  • Prune decision trees to avoid overfitting
  • Manipulate sample distribution in nodes and leaves

Cross Validation and Ensemble Techniques for Decision Trees 2h

Lesson Objectives
  • Apply cross validation techniques to decision trees.
  • Find the optimal parameters of decision trees using grid search.
  • Identify the differences between decision trees and random forest models.
  • Develop and customize random forest models.
  • Optimize the parameters of random forest.
  • Identify the differences between random forest and extra trees.
  • Determine the advantages and disadvantages of decision trees.

Guided Project: Predicting Employee Productivity Using Tree Models 1h

Lesson Objectives
  • Clean and adapt a dataset for use in a decision tree
  • Build and visualize a decision tree to determine key features
  • Evaluate your trees using different metrics
  • Optimize trees by adjusting their parameters
  • Explain the results of a tree model to a non-technical audience

Projects in this course

Guided Project: Predicting Employee Productivity Using Tree Models

For this project, we’ll step into the role of data scientists to determine the best working conditions for maximizing productivity in a garment factory using decision trees and random forests in Python.

The Dataquest guarantee

Guarantee

Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.

Money

We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.

Master skills faster with Dataquest

Go from zero to job-ready

Go from zero to job-ready

Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.

Build your project portfolio

Build your project portfolio

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

Challenge yourself with exercises

Challenge yourself with exercises

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

Showcase your path certification

Showcase your path certification

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

Grow your career with
Dataquest.

98%
of learners recommend
Dataquest for career advancement
4.85
Dataquest rating
SwitchUp Best Bootcamps
$30k
Average salary boost
for learners who complete a path
Aaron

Aaron Melton

Business Analyst at Aditi Consulting

“Dataquest starts at the most basic level, so a beginner can understand the concepts. I tried learning to code before, using Codecademy and Coursera. I struggled because I had no background in coding, and I was spending a lot of time Googling. Dataquest helped me actually learn.”

Jessi

Jessica Ko

Machine Learning Engineer at Twitter

“I liked the interactive environment on Dataquest. The material was clear and well organized. I spent more time practicing then watching videos and it made me want to keep learning.”

Victoria

Victoria E. Guzik

Associate Data Scientist at Callisto Media

“I really love learning on Dataquest. I looked into a couple of other options and I found that they were much too handhold-y and fill in the blank relative to Dataquest’s method. The projects on Dataquest were key to getting my job. I doubled my income!”

Join 1M+ data learners on
Dataquest.

1

Create a free account

2

Choose a learning path

3

Complete exercises and projects

4

Advance your career

Start learning today