Tidymodels in R: Building tidy machine learning models from Coursera

This guided project aims to empower data professionals to build tidy machine-learning models in R.

In this 2-hour project-based course, you will be working in the context of a real-world scenario as part of a data-science team tasked with reducing hospital readmissions for a leading healthcare organization. Through hands-on practice, you’ll learn to preprocess clinical data and train and evaluate machine learning models. By the end of this learning experience, you'll have created a comprehensive machine-learning pipeline tailored to predict hospital readmissions.

To succeed, you'll need a good understanding of R programming language, including data manipulation and visualization using tidyverse packages and some knowledge of machine learning concepts.

No prior experience with Tidymodels is required, making it accessible to anyone interested in leveraging data science for healthcare analytics. Join us on this transformative journey and become equipped to make a meaningful impact on patient care outcomes through data-driven insights.

What's inside

Syllabus

Project Overview

This guided project aims to empower data professionals to build tidy machine-learning models in R. In this 2-hour project-based course, you will be working in the context of a real-world scenario as part of a data-science team tasked with reducing hospital readmissions for a leading healthcare organization. Through hands-on practice, you’ll learn to preprocess clinical data and train and evaluate machine learning models. By the end of this learning experience, you'll have created a comprehensive machine-learning pipeline tailored to predict hospital readmissions. To succeed, you'll need a good understanding of R programming language, including data manipulation and visualization using tidyverse packages and some knowledge of machine learning concepts. No prior experience with Tidymodels is required, making it accessible to anyone interested in leveraging data science for healthcare analytics. Join us on this transformative journey and become equipped to make a meaningful impact on patient care outcomes through data-driven insights.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Course is project-based, which is a widely accepted way to develop key skills in data science

Touches on industry-standard tools for visualizing and manipulating data, including tidyverse family of packages

Provides a strong foundation for those interested in the intersection of data science and healthcare

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 Tidymodels in R: Building tidy machine learning models with these activities:

Brush Up on R Programming

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Refreshes your knowledge of R programming and its libraries.

Browse courses on R Programming

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Review basic R syntax and data structures.
Practice data manipulation and visualization using tidyverse packages.
Complete online exercises or tutorials to reinforce your understanding.

Read 'Hands-On Machine Learning with R'

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Provides a comprehensive foundation in machine learning concepts and techniques.

View Hands-On Machine Learning with R on Amazon

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Obtain a copy of the book.
Read and understand the chapters relevant to the course topics.
Complete the exercises and examples provided in the book.

Join a Study Group

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Provides opportunities for discussion, collaboration, and knowledge sharing.

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Connect with other students in the course or online.
Establish a regular meeting schedule for discussing course materials and projects.
Share notes, insights, and perspectives with the group.

Five other activities

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Develop a Machine Learning Cheat Sheet

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Summarizes key concepts and techniques for easy reference.

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Identify important concepts and techniques covered in the course.
Condense the information into concise and easy-to-understand notes.
Create a cheat sheet in a format that is easily accessible for reference.

Explore Advanced Tidymodels Tutorials

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Enhances understanding of Tidymodels and its applications.

Browse courses on Tidymodels

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Identify areas where you wish to deepen your understanding.
Search for online tutorials or documentation that cover these topics.
Follow the tutorials, taking notes and experimenting with the code.

Attend a Machine Learning Workshop

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Offers practical hands-on experience and exposure to industry experts.

Browse courses on Machine Learning

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Research and identify relevant workshops in your area.
Register for a workshop that aligns with your learning goals.
Attend the workshop, actively participate, and network with attendees.

Practice on Sample Dataset

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Reinforces concepts covered in the course through hands-on practice.

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Obtain sample dataset provided in the course materials.
Preprocess and clean the data to prepare it for analysis.
Apply machine learning techniques to build and evaluate models.

Volunteer as a Course Mentor

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Strengthens your understanding by teaching and assisting others.

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Reach out to the instructor or course organizers.
Volunteer to assist students with course materials and projects.
Provide guidance, answer questions, and facilitate discussions.

Career center

Learners who complete Tidymodels in R: Building tidy machine learning models will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists develop machine learning models that solve real-world problems. They use their extensive knowledge of computer science and statistics to work with large volumes of data. Tidymodels in R: Building tidy machine-learning models is a course that teaches the fundamentals of machine learning in R, one of the most popular programming languages for data science. This course will help you build a solid foundation in machine learning, which is essential for success as a Data Scientist.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers build, deploy, and maintain machine learning models. They work closely with Data Scientists to ensure that models are accurate and reliable. This course will teach you the skills you need to build and deploy machine learning models in R. It will also teach you how to evaluate the performance of your models and make improvements as needed.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts use data to solve business problems. They work with data from a variety of sources to identify trends and patterns. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders.

See salaries and explore the career path for Data Analyst

Healthcare Analyst

Healthcare Analysts use data to improve the quality and efficiency of healthcare delivery. They work with data from a variety of sources to identify trends and patterns. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders. In addition, this course will provide you with a foundation in machine learning, which is increasingly used in healthcare to improve patient outcomes.

See salaries and explore the career path for Healthcare Analyst

Business Analyst

Business Analysts use data to solve business problems. They work with data from a variety of sources to identify trends and patterns. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians use data to solve problems in a variety of fields, including healthcare, finance, and marketing. They work with data from a variety of sources to identify trends and patterns. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders.

See salaries and explore the career path for Statistician

Financial Analyst

Financial Analysts use data to make investment decisions. They work with data from a variety of sources to identify trends and patterns. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders.

See salaries and explore the career path for Financial Analyst

Market Researcher

Market Researchers use data to understand consumer behavior. They work with data from a variety of sources to identify trends and patterns. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders.

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Operations Research Analyst

Operations Research Analysts use data to improve the efficiency of operations. They work with data from a variety of sources to identify trends and patterns. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They work with data from a variety of sources to build software that meets the needs of users. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders.

See salaries and explore the career path for Software Engineer

Web Developer

Web Developers design and develop websites. They work with data from a variety of sources to build websites that are both visually appealing and functional. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders.

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Database Administrator

Database Administrators manage and maintain databases. They work with data from a variety of sources to ensure that data is accurate and accessible. This course will teach you the skills you need to clean, analyze, and visualize data. It will also teach you how to communicate your findings to stakeholders.

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Data Entry Clerk

Data Entry Clerks enter data into computer systems. They work with data from a variety of sources to ensure that data is accurate and complete. This course may be useful for Data Entry Clerks who want to learn more about data analysis and visualization.

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Office Administrator

Office Administrators provide administrative support to businesses. They work with data from a variety of sources to ensure that the office runs smoothly. This course may be useful for Office Administrators who want to learn more about data analysis and visualization.

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Customer Service Representative

Customer Service Representatives provide support to customers. They work with data from a variety of sources to resolve customer issues. This course may be useful for Customer Service Representatives who want to learn more about data analysis and visualization.

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