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Charlotte Wickham

In this course, you’ll see the entire workflow that data professionals use to produce their R analytics solutions.

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In this course, you’ll see the entire workflow that data professionals use to produce their R analytics solutions.

You’ve been given the task of building your next analytics report in R. Your colleague has even shared some R code they think will help. But where do you start? You’re not even sure what to do with the .R file they shared. In this course, Building Your First R 3 Analytics Solution, you’ll see the entire workflow that data professionals use to produce their R analytics solutions. First, you’ll start right at the beginning — setting up your own computer to run R code. Next, you’ll learn how to run, read, and write R code in RStudio. Finally, you'll discover how to organize your work with RStudio projects and how to communicate your work with R Markdown. By the end of the course, you’ll have not only produced a shareable report with R Markdown, you’ll have built your project so that anyone else can recreate the report too. You’ll be using the same tools and workflows as R professionals, and along the way, you’ll start building habits that ensure your analysis is organized, documented, and reproducible.

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What's inside

Syllabus

Course Overview
Setting up Your Computer to Use R
Working with R Code in RStudio
Organizing Your Work with RStudio Projects
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Communicating and Documenting Your Analysis with R Markdown

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Introduces a structured and documented workflow, making analysis reproducible and accessible
Provides guidance on setting up your computer for R programming, ensuring a smooth installation and troubleshooting process
Utilizes industry-standard tools like RStudio, aligning with professional practices in data analytics
Teaches the fundamentals of reading, writing, and running R code, building a strong foundation for further learning
Covers essential topics in organizing and documenting analysis, ensuring clarity and efficiency throughout the project lifecycle

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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 Building Your First R 3 Analytics Solution with these activities:
Organize and Review Course Materials
Enhance your understanding by organizing and reviewing the course materials regularly.
Show steps
  • Create a dedicated folder or notebook for the course
  • Regularly review lecture notes, assignments, and any additional materials provided
RStudio Code Practice
Enhance your proficiency in using RStudio's interface and executing R code.
Browse courses on RStudio
Show steps
  • Navigate RStudio's interface, practice writing and executing R code in the console
  • Utilize RStudio's debugging tools to troubleshoot and fix errors in your code
  • Explore RStudio's packages and learn how to install and load them
Join a Study Group or Online Forum
Engage with peers to clarify concepts, share insights, and learn from others' experiences.
Show steps
  • Identify or create a study group with classmates or connect with peers in online forums
  • Discuss course topics, work on assignments together, and provide feedback to each other
Two other activities
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Show all five activities
Build a Small R Analytics Project
Solidify your understanding by applying your R analytics skills to a small project.
Show steps
  • Identify a small dataset or problem that can be analyzed using R
  • Write R code to clean, explore, and analyze the data
  • Create visualizations to present your findings and insights
Contribute to Open-Source R Projects
Gain practical experience and contribute to the R community by participating in open-source projects.
Show steps
  • Identify R projects on platforms like GitHub that align with your interests and skills
  • Read the project documentation and contribute bug reports or feature suggestions
  • If possible, contribute code or documentation to the project

Career center

Learners who complete Building Your First R 3 Analytics Solution will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst uses R and other programming languages to gather, analyze, and interpret data. They may also develop visualizations to communicate their findings. This course can help you get started with R and build a foundation for a career as a Data Analyst. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Data Scientist
A Data Scientist uses R and other programming languages to build and evaluate models. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Data Scientists who want to learn more about R and how to use it for data analysis. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Statistician
A Statistician uses R and other programming languages to analyze data and draw conclusions. They may also develop models to predict future outcomes. This course can be helpful for aspiring Statisticians who want to learn more about R and how to use it for data analysis. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Machine Learning Engineer
A Machine Learning Engineer uses R and other programming languages to develop and deploy machine learning models. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Machine Learning Engineers who want to learn more about R and how to use it for machine learning. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Data Engineers who want to learn more about R and how to use it for data engineering. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Software Engineers who want to learn more about R and how to use it for software development. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Business Analyst
A Business Analyst uses R and other programming languages to analyze data and make recommendations for businesses. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Business Analysts who want to learn more about R and how to use it for business analysis. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Financial Analyst
A Financial Analyst uses R and other programming languages to analyze data and make recommendations for investors. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Financial Analysts who want to learn more about R and how to use it for financial analysis. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Marketing Analyst
A Marketing Analyst uses R and other programming languages to analyze data and make recommendations for marketing campaigns. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Marketing Analysts who want to learn more about R and how to use it for marketing analysis. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Operations Research Analyst
An Operations Research Analyst uses R and other programming languages to analyze data and make recommendations for businesses. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Operations Research Analysts who want to learn more about R and how to use it for operations research. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Risk Analyst
A Risk Analyst uses R and other programming languages to analyze data and make recommendations for businesses. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Risk Analysts who want to learn more about R and how to use it for risk analysis. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Data Journalist
A Data Journalist uses R and other programming languages to analyze data and create visualizations. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Data Journalists who want to learn more about R and how to use it for data journalism. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Quantitative Analyst
A Quantitative Analyst uses R and other programming languages to analyze data and make recommendations for investors. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Quantitative Analysts who want to learn more about R and how to use it for quantitative analysis. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Actuary
An Actuary uses R and other programming languages to analyze data and make recommendations for insurance companies. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Actuaries who want to learn more about R and how to use it for actuarial science. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.
Economist
An Economist uses R and other programming languages to analyze data and make recommendations for governments and businesses. They may also work with data to identify trends and develop insights. This course can be helpful for aspiring Economists who want to learn more about R and how to use it for economics. You will learn how to set up your computer to use R, work with R code in RStudio, organize your work with RStudio projects, and communicate your work with R Markdown.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Building Your First R 3 Analytics Solution.
Provides a comprehensive introduction to the R programming language and its use in data science. It covers topics such as data manipulation, visualization, and statistical modeling.
Provides a comprehensive introduction to the R programming language and its use in data science. It covers topics such as data manipulation, visualization, and statistical modeling.
Provides a comprehensive introduction to causal inference in statistics. It covers topics such as graphical models, structural equation modeling, and counterfactuals.
Provides a comprehensive introduction to predictive modeling in R. It covers topics such as supervised learning, unsupervised learning, and model evaluation.
Provides a comprehensive introduction to Bayesian analysis in R. It covers topics such as Bayesian statistics, Bayesian modeling, and Bayesian inference.
Provides a comprehensive introduction to machine learning for hackers. It covers topics such as supervised learning, unsupervised learning, and model evaluation.
Provides a comprehensive introduction to statistical inference in R. It covers topics such as hypothesis testing, confidence intervals, and regression analysis.
Provides a comprehensive introduction to natural language processing in R. It covers topics such as text preprocessing, text mining, and sentiment analysis.
Provides a comprehensive guide to the R Markdown language, a powerful tool for creating dynamic, reproducible reports and documents in R.

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