Coding in R for Data

Leonard N. Stern School of Business

Leonard N. Stern School of Business

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Who should attend

Although there are no formal education or background requirements, this course is designed for participants who meet the criteria below. While we strongly encourage global participation, please note that all courses are taught in English. Proficiency in written and spoken English is required.

  • Years of Experience – Participants with all levels of work experience are welcome to attend
  • Job Functions – Ideal for any job function
  • Prerequisites – Intended for individuals with no experience in R or programming

About the course

In today's age of analytics, the ability to transform data into information and actionable insights is essential. Coding in R for Data provides students with an understanding of how to import, format, understand, and communicate their data findings in R, a common statistical language utilized in a diverse range of industries.

In this 4-week course, students will learn how to program in R for effective data manipulation and visualization. Students will import, transform, and manipulate datasets for various analytical purposes. Students will develop the ability to create control structures, such as loops and conditional statements to traverse, sort, merge, and evaluate data. This course is designed for those who have no experience in R or programming.

Program Takeaways

  • R Programming Basics – Learn coding basics for working with data in the R programming language
  • Preparing Data in R – Clean, format, and manipulate data
  • Report & Present Data in R – Build apps, create reports, and deliver presentations of your data in R

Agenda

Getting Started

Course Access

In order to access the course, you will receive login credentials via email on the start date of the course. Activation instructions for your login credentials will be provided.

Required Books

Wickham, H. & Grolemund, G. (2018). R for Data Science. O'Reilly: New York. (free, available digitally); Sosulski, K. (2019.) R Fundamentals. Bookdown: New York. (free, available digitally)

Live Online Meetups with Faculty

Our live online meetups provide you with the opportunity to engage face-to-face with Professor Sosulski. Please note that all online meetups are recorded and available for your viewing at a later time. Missing a meetup will not impact your grade, however, we recommend attending all sessions.

Workload

Please expect to invest about 10 to 12 hours of your time per week to course lessons, exercises, and assignments.

Week 1: Coding Basics

  • Introduction to R Programming
  • Data Structures, Variables, and Data Types

Week 2: Data Exploration

  • Packages, Scripts, and Rmarkdown
  • Descriptive Statistics in R

Week 3: Data Presentaton

  • Reporting and Visualization in Rmarkdown
  • Data Cleaning and Formatting for Messy Data

Week 4: Data Application

  • Functions, Iterations, and Conditionals
  • Interactive Applications Using Rshiny

Experts

Kristen Sosulski

Kristen Sosulski is a Clinical Associate Professor of Information, Operations and Management Sciences at New York University Stern School of Business. She is also the Director of Education for the W.R. Berkley Innovation Lab. She teaches Data Visualization, Operations in Panama, Ops in NYC, the c...

Videos and materials

Coding in R for Data at Leonard N. Stern School of Business

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Disclaimer

Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with any business school or university.

Full disclaimer.

Read more about Business Analytics

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Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.

We are happy to help you find a suitable online alternative.