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Summer school in Data-driven Publishing

Опис

From June 10 to June 17, Kyiv School of Economics will host a summer school in “Data-driven Publishing: Reproducible Research using R, Quarto, and Github”

 

Instructor – Dr. Arthur Small, University of Virginia

 

All classes will be on-site: physical presence is required. 

 

IF YOU WANT TO PARTICIPATE PRESS HERE

 

Summary: 

All analysts need to present their results in multiple formats: articles, slide decks, web sites, and so on. Traditional workflows for creating and publishing documents rely heavily on manual workflows, e.g., copy-and-paste. Traditional workflows are poorly suited to data-intensive analytic projects. 

 

This course will provide an introduction to an entirely different and better approach to scientific and technical publishing that is code-driven and reproducible. Reproducible workflows are appropriate to creating and presenting the results of data analysis. They are increasingly indispensable for professionals working in data science and allied data-intensive, analytic roles.

 

The course will emphasize hands-on project development. On the first day, each student will create and publish a professional webpage for themselves. By the end of the course, students will create and present a project that integrates data analysis in a real application, preferably related to the reconstruction of Ukraine. Prizes will be awarded for the top 3 presentations.

 

Who it can be interesting for: Advanced undergrad and masters students in economics or business, social science, data analysis, journalism with at least some exposure to coding, preferably in R. 

 

The purpose of the course is to help students improve their ability to present the results of data analysis. Early career researchers will also be accepted.

 

Project based learning. Each student is expected to complete an independent projects by the end of the summer school.

 

What students will learn:

  • Main principles of reproducible research and literate programming for scientific and technical publishing
  • Basic introduction to coding in R
  • How to execute projects using R, Github and Quarto
  • How to work with Markdown 
  • How to arrange figures, tables, diagrams, citations & footnotes, cross references, and article layouts using code
  • How to publish findings in different formats using code (web, documents, slides)

 

           Schedule:

Friday June 10 – Friday June 17:  

  • Every day 10:00-13:00: in-class instruction
  • Every day 14:00-16:00: small-group and individual collaboration and feedback
  • Friday June 17, 10:00-12:00: Student presentations of projects; announcement of award winners

         *All classes will be on-site: physical presence is required. 

 

What students will get upon the successful completion of the school:

  • 2 ECTS credits
  • Top 3 projects will receive 10% discounts to study at KSE MA program in economics

 

Prerequisites: 

 

  1. Participants must submit the form (HERE) before June 8
  2. Participants must bring their own laptops to all sessions
  3. Having an interest to attend MA or PhD programs in economics, social science, computer science in Ukraine or abroad will be a benefit

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About the instructor:

Arthur Small

An economist and data scientist specializing in applications to energy, environment, weather and climate. He has held faculty positions at Columbia Business School, Columbia School of International and Public Affairs, the Penn State College of Earth and Mineral Sciences, and (visiting) the Dyson School of Applied Economics and Management at Cornell University, and has worked as a commercial data scientist. He has published in venues including Journal of Political Economy, Review of Economics and Statistics, and Journal of Environmental Economics and Management. Small’s research has been supported by the U.S. National Science Foundation (NSF), the U.S. Environmental Protection Agency, and other entities. He has served on review panels for the U.S. National Academy of Sciences, the NSF, and others. His research has been recognized by the Quality of Research Discovery Award from the Agricultural and Applied Economics Association. His training includes an A.B. in Mathematics from Columbia University, M.S. in Mathematics from Cornell University, and a Ph.D. in Agricultural and Resource Economics from the University of California, Berkeley. He currently serves as Lecturer in the School of Engineering and Applied Sciences at the University of Virginia.