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 basic knowledge of Microsoft Excel and no prior experience in R or programming
About the course
Coding and Visual Analytics provides students with the foundational skills needed to become a data literate manager. Learn the basics of programming for data preparation, understanding, and communication. Build core skills in the R programming language for data importing, formatting, and analysis. Use Tableau, a leading business intelligence platform, to create robust visualizations and dashboards that communicate your findings.
For the first four weeks of this program, students will learn how to program in R for effective data manipulation and visualization. They will also develop the ability to create control structures, such as loops and conditional statements, to traverse, sort, merge, and evaluate data. The following eight weeks of the program will focus on techniques for data preparation — how to choose, create, and edit graphics, as well as best practices for presenting your visualizations.
- Statistical Programming – Go beyond working with data in Excel. Learn a powerful statistical programming package to format, manipulate, analyze, and visualize data.
- Data Presentation – Present your data so it is compelling and easy to understand.
- Data Analysis and Reporting – Explore, analyze, and share your data findings. Learn to build dynamic reports and interactive apps.
Coding in R for Data
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
Coding in R for Data
Week 3: Data Presentation * Reporting and Visualization in Rmarkdown * Data Cleaning and Formatting for Messy Data
Week 4: Data Application * Functions, Iteration, and Conditionals * Interactive Applications Using Rshiny
Week 5: Essentials of Visualizing Data * Introduction to Data Graphics and Design * Design + Audience
Week 6: Visualizing Comparisons * Categorical Data, Graphics and Design * The Report
Week 7: Visualizing Locations * Geospatial Data, Graphics and Design * The Dashboard
Week 8: Visualizing Time * Temporal Data, Graphics and Design * The Presentation
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...
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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.