Leonard N. Stern School of Business

Coding + Visual Analytics

Available dates

Jan 27—Apr 27, 2020
Online
USD 2992

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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.

Program Takeaways

  • 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.

Agenda

WEEKS 1-2

Coding in R for Data

Week 1 (January 27th - February 2nd): Coding Basics

  • Introduction to R Programming
  • Data Structures, Variables, and Data Types
  • Live Online Meetup 1: January 30th at 8:00 PM ET

Week 2 (February 3rd - February 9th): Data Exploration

  • Packages, Scripts, and Rmarkdown
  • Descriptive Statistics in R
  • Live Online Meetup 2: February 6th at 8:00 PM ET

WEEKS 3-4

Coding in R for Data

Week 3 (February 10th - February 16th): Data Presentation

  • Reporting and Visualization in Rmarkdown
  • Data Cleaning and Formatting for Messy Data
  • Live Online Meetup 3: February 13th at 8:00 PM ET

Week 4 (February 17th - February 21st): Data Application

  • Functions, Iterations, and Conditionals
  • Interactive Applications Using Rshiny
  • Live Online Meetup 4: February 20th at 8:00 PM ET
  • BREAK: February 24th - March 1st

WEEKS 5-6

Visualizing Data

Week 5 & 6 (March 2nd - March 15th): Essentials of Visualizing Data

  • Introduction
  • Live Online Meetup 5: March 5th at 8:00 PM ET
  • Graphics + Data
  • Live Online Meetup 6: March 12th at 8:00 PM ET
  • Design + Audience

WEEKS 7-8

Visualizing Data Weeks 7 & 8 (March 16th - March 29th): Visualizing Comparisons

  • Categorical Data Graphics
  • Categorical Data Types
  • Live Online Meetup 7: March 19th at 8:00 PM ET
  • Design Principles for Categorical Data Graphics
  • Live Online Meetup 8: March 26th at 8:00 PM ET
  • Pitch: The Report

WEEKS 9-10

Visualizing Data Weeks 9 & 10 (March 30th - April 12th): Visualizing Locations

  • Geospatial Data Graphics
  • Geospatial Data Types
  • Live Online Meetup 9: April 2nd at 8:00 PM ET
  • Design Principles for Geospatial Data Graphics
  • Live Online Meetup 10: April 9th at 8:00 PM ET
  • Pitch: Web Dashboard

WEEKS 11-12

Visualizing Data

Weeks 11 & 12 (April 13th - April 26th): Visualizing Time

  • Temporal Data Graphics
  • Temporal Data Types
  • Live Online Meetup 11: April 16th at 8:00 PM ET
  • Design Principles for Temporal Data Graphics
  • Live Online Meetup 12: April 23rd at 8:00 PM ET
  • Pitch: The Presentation

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

Trust the experts

Kristen Sosulski

Biography 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...

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