Winter School: Data Science Tools

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The eScience Institute offers the annual Winter School to students and lecturers interested in developing basic skills and knowledge of the tools used in data science. Gaining literacy in topics such as Python, R, Jupyter, and reproducible environments can be beneficial beyond STEM, including areas like global or public health, public policy, social sciences, social work, international relations, and business management.

There are no prerequisites to take this course and there is no credit offered. UW faculty, undergraduate students, and graduate students are welcome to apply.

The deadline to apply is January 4th, 2024

Winter School 2024 classes will be offered from 5:00 to 7:00 p.m. twice a week on Tuesdays and Thursdays. The same class material will be taught on both days so that participants can choose the day that works best for their schedule.

Class 1: January 9th & 11th, 5-7 pm

Python and R: This class will give an overview of Python and R simple data structures in a comparative way (vectors, lists, dictionaries, tuples, sets, data frames). This first session will  focus on differences between these languages, and will help students with related procedures such as installation and environments, as well as user interfaces.

Class 2: January 16th & 18th, 5-7 pm

Python and Jupyter: This class will give an overview of Python capabilities for different data management processes (collection, saving, and  pre-processing). The output of the session will be a file to be imported into R for statistical work.

Class 3: January 23rd & 26th, 5-7 pm

R and RStudio/Posit: This class will introduce students to R programming language. It will focus on its capabilities for statistical computing and visualization.

Class 4: January 30th & February 1st, 5-7 pm

Reproducible Environments: This last class will organize the work done in the previous session. It will teach students how to combine R and tools like Latex/Markdown (for document preparation), Github (for organizing data repositories),  Zotero (to manage references), and Zenodo (to create DOIs). All of these combined ensure  a reproducible paper or blog post.

About the Instructor

Jose Manuel Magallanes, PhD is a Senior Data Science Fellow at the eScience Institute, and a Visiting Professor at Evans School of Public Policy and Governance at the University of Washington. Additionally, he is a Professor of Political Science and Government at Pontificia Universidad Católica del Peru, Director of the Institute for Social Analytics and Strategic Intelligence, and Professor and Head of the Interdisciplinary Group for Public Policy Foresight.

The Winter School is offered free of charge thanks to the support of the eScience Institute and its funding partners. Professor Magallanes acknowledges the material has been developed thanks to his visiting at the eScience Institute and Evans School at UW, and to the work he develops at GI3P.