Decision Tree Classifier for Beginners in R from Coursera

By the end of this 2-hour long project, you will understand the basic intuition behind the decision tree algorithm and how it works. To build the model, we will divide or partition the data into the training and testing data set. Finally, you will learn how to evaluate the model’s performance using metrics like Accuracy, Sensitivity, Specificity, F1-Score, and so on. By extension, you will learn how to save the trained model on your local system.

Although you do not need to be a data analyst expert or data scientist to succeed in this guided project, it requires a basic knowledge of using R, especially writing R syntaxes. Therefore, to complete this project, you must have prior experience with using R. If you are not familiar with working with using R, please go ahead to complete my previous project titled: “Getting Started with R”. It will hand you the needed knowledge to go ahead with this project on Decision Tree. However, if you are comfortable with working with R, please join me on this beautiful ride! Let’s get our hands dirty!

What's inside

Syllabus

Project Overview

Welcome to this project-based course Decision Tree Classifier for Beginners in R. This is a hands-on project that introduces beginners to the world of statistical modeling. In this project, you will learn how to build decision tree models using the tree and rpart libraries in R. We will start this hands-on project by importing the Sonar data into R and exploring the dataset. By the end of this 2-hour long project, you will understand the basic intuition behind the decision tree algorithm and how it works. To build the model, we will divide or partition the data into the training and testing data set. Finally, you will learn how to evaluate the model’s performance using metrics like Accuracy, Sensitivity, Specificity, F1-Score, and so on. By extension, you will learn how to save the trained model on your local system. Although you do not need to be a data analyst expert or data scientist to succeed in this guided project, it requires a basic knowledge of using R, especially writing R syntaxes. Therefore, to complete this project, you must have prior experience with using R. If you are not familiar with working with using R, please go ahead to complete my previous project titled: “Getting Started with R”. It will hand you the needed knowledge to go ahead with this project on Decision Tree. However, if you are comfortable with working with R, please join me on this beautiful ride! Let’s get our hands dirty!

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

- Teaches skills, knowledge, and/or tools that are highly relevant to industry

- Teaches skills, knowledge, and/or tools that are highly relevant in an academic setting

- Develops professional skills or deep expertise in a particular topic or set of topics

- Designed for beginners

- Builds a strong foundation for beginners

- Teaches beginner-friendly material

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Decision Tree Classifier for Beginners in R with these activities:

Follow a Guided Tutorial on Decision Tree Algorithms

Show steps

Provides step-by-step instructions and exercises to master decision tree algorithms.

Browse courses on Decision Trees

Show steps

Choose a reputable online platform or resource for guided tutorials.
Select a tutorial that aligns with your level of understanding.
Follow the tutorial's instructions and complete the exercises.

Join a Decision Tree Study Group

Show steps

Provides a collaborative learning environment to discuss and clarify concepts.

Browse courses on Decision Trees

Show steps

Find peers or classmates interested in forming a study group.
Establish a regular meeting schedule and set goals.
Work together to review concepts, solve problems, and share knowledge.

Find a Mentor Experienced in Decision Trees

Show steps

Provides access to personalized guidance and support from an experienced professional.

Browse courses on Decision Trees

Show steps

Identify potential mentors through networking or online platforms.
Reach out to your selected mentors and express your interest.
Establish a mentoring relationship and schedule regular meetings.

Five other activities

Expand to see all activities and additional details

Show all eight activities

Read 'Decision Trees for Beginners' by Haibo He

Show steps

Provides a conceptual understanding of decision trees and their role in machine learning.

View Self-Adaptive Systems for Machine Intelligence on Amazon

Show steps

Read through the book's main topics and concepts introduced.
Solve practice questions and exercises in the book.

Solve Decision Tree Practice Problems on HackerRank

Show steps

Reinforces understanding of decision tree concepts through practical problem-solving.

Browse courses on Decision Trees

Show steps

Sign up for a HackerRank account and join the Decision Tree contest.
Solve the practice problems related to Decision Tree and Machine Learning.
Review your solutions and analyze your performance.

Attend a Decision Tree Workshop

Show steps

Provides structured guidance and hands-on practice under the guidance of experts.

Browse courses on Decision Trees

Show steps

Research and find upcoming Decision Tree workshops.
Register and attend the workshop.
Actively participate in the workshop activities and discussions.

Create a Decision Tree Infographic

Show steps

Enhances visual comprehension and understanding of decision tree concepts and applications.

Browse courses on Decision Trees

Show steps

Gather relevant information and data related to Decision Trees.
Organize and structure the information into a visually appealing infographic.
Use design tools or software to create the infographic.

Develop a Decision Tree Model for a Real-World Dataset

Show steps

Applies decision tree techniques to solve practical problems and gain hands-on experience.

Browse courses on Decision Trees

Show steps

Identify a suitable real-world dataset related to your field of interest.
Load and explore the dataset to understand its characteristics.
Train a decision tree model on the prepared dataset.
Evaluate the performance of the model and refine it as necessary.

Career center

Learners who complete Decision Tree Classifier for Beginners in R will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models. Decision tree classifiers are a widely used machine learning algorithm that machine learning engineers use to solve a variety of problems. This course can help machine learning engineers gain a deeper understanding of the principles and applications of decision tree classifiers, which will be essential for their success in the field.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use statistical and machine learning techniques to extract insights from data. Decision tree classifiers are a fundamental machine learning algorithm that data scientists use for a variety of tasks, such as classification and prediction. This course can help aspiring data scientists build a strong foundation in the use of decision tree classifiers, which will be highly valuable in their day-to-day work.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst collects, processes, and analyzes data to help businesses make informed decisions. Knowledge of decision tree classifiers is highly applicable to the role of a data analyst as they provide a simple and effective way to identify patterns and trends in data. This course can help build a foundation for success in data analysis by providing learners with a solid understanding of the principles and applications of decision tree classifiers.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians collect, analyze, interpret, and present data. Decision tree classifiers are a powerful tool for statisticians to use for classification and prediction tasks. This course can provide statisticians with a solid understanding of the principles and applications of decision tree classifiers, which will be highly beneficial in their work.

See salaries and explore the career path for Statistician

Business Analyst

Business Analysts use data to help businesses make better decisions. Decision tree classifiers are a valuable tool for business analysts to use to identify patterns and trends in data that can help businesses improve their operations. This course can help business analysts develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Business Analyst

Market Researcher

Market Researchers collect and analyze data to understand consumer behavior. Decision tree classifiers are a valuable tool for market researchers to use to identify patterns and trends in consumer behavior that can help businesses develop better products and services. This course can help market researchers develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Market Researcher

Operations Research Analyst

Operations Research Analysts use data to improve the efficiency and effectiveness of business operations. Decision tree classifiers are a valuable tool for operations research analysts to use to identify patterns and trends in data that can help businesses improve their operations. This course can help operations research analysts develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Operations Research Analyst

Financial Analyst

Financial Analysts use data to make investment decisions. Decision tree classifiers are a useful tool for financial analysts to use to identify patterns and trends in financial data that can help them make better investment decisions. This course can help financial analysts develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Financial Analyst

Risk Analyst

Risk Analysts use data to identify and assess risks. Decision tree classifiers are a valuable tool for risk analysts to use to identify patterns and trends in data that can help businesses mitigate risks. This course can help risk analysts develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Risk Analyst

Data Engineer

Data Engineers design, build, and maintain data pipelines. Decision tree classifiers are a valuable tool for data engineers to use to improve the quality and efficiency of data pipelines. This course can help data engineers develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

Quantitative Analysts use data to make investment decisions. Decision tree classifiers are a valuable tool for quantitative analysts to use to identify patterns and trends in financial data that can help them make better investment decisions. This course can help quantitative analysts develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Quantitative Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. Decision tree classifiers are a valuable tool for software engineers to use to improve the performance and efficiency of software applications. This course can help software engineers develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Software Engineer

Project Manager

Project Managers are responsible for planning, executing, and closing projects. Decision tree classifiers are a valuable tool for project managers to use to identify and mitigate risks. This course can help project managers develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Project Manager

Product Manager

Product Managers are responsible for the development and launch of new products. Decision tree classifiers are a valuable tool for product managers to use to understand customer needs and preferences. This course can help product managers develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Product Manager

Business Consultant

Business Consultants advise businesses on how to improve their operations. Decision tree classifiers are a valuable tool for business consultants to use to identify areas for improvement. This course can help business consultants develop the skills needed to use decision tree classifiers effectively, which will be a valuable asset in their careers.

See salaries and explore the career path for Business Consultant