Date/Time

Date(s) - 01/23/2023 - 02/13/2023
11:30 am - 2:00 pm

Registration coming soon!

Photo of Jose Manuel MagallanesDirector:
Jose Manuel Magallanes, PhD

  • Visiting Professor at Evans School of Public Policy and Governance
    eScience Institute Senior Data Science Fellow
  • Professor of Political Science and Government at Pontificia Universidad Católica del Peru (PUCP).
  • Director of the Institute for Social Analytics and Strategic Intelligence (PULSO PUCP)
  • Professor and Head of the Interdisciplinary Group for Public Policy Foresight (GI3P),

Course Description:
The University of Washington eScience Institute offers this winter school to students and lecturers in Global/Public Health, Public Policy, Social Sciences, Social Work, International Relations and Business Management  who are interested in developing basic skills and knowledge of the tools used in data science.

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

The deadline to submit applications is January 26th.

Schedule:

Class 1: Monday, January 20th (11:30 – 14:00)
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, dataframes). 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: Monday, January 27th (11:30 – 14:00)
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: Monday, February 6th (11:30 – 14:00)
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: Monday, February 13th (11:30 – 14:00)
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 og these combined ensure  a reproducible paper or blog post.

 

Office hours for this course:
Please email to make an appointment magajm@uw.edu

Note:
Classes are offered at the EScience Studio, there is no virtual participation. However, tutoring/office hours can be virtually.

This 2023 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 eScience and Evans School at UW, and to the work he develops at GI3P.

Winter School on Data Science Tools 2023

­

Date/Time

Date(s) - 01/23/2023 - 02/13/2023
11:30 am - 2:00 pm

Registration coming soon!

Photo of Jose Manuel MagallanesDirector:
Jose Manuel Magallanes, PhD

  • Visiting Professor at Evans School of Public Policy and Governance
    eScience Institute Senior Data Science Fellow
  • Professor of Political Science and Government at Pontificia Universidad Católica del Peru (PUCP).
  • Director of the Institute for Social Analytics and Strategic Intelligence (PULSO PUCP)
  • Professor and Head of the Interdisciplinary Group for Public Policy Foresight (GI3P),

Course Description:
The University of Washington eScience Institute offers this winter school to students and lecturers in Global/Public Health, Public Policy, Social Sciences, Social Work, International Relations and Business Management  who are interested in developing basic skills and knowledge of the tools used in data science.

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

The deadline to submit applications is January 26th.

Schedule:

Class 1: Monday, January 20th (11:30 – 14:00)
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, dataframes). 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: Monday, January 27th (11:30 – 14:00)
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: Monday, February 6th (11:30 – 14:00)
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: Monday, February 13th (11:30 – 14:00)
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 og these combined ensure  a reproducible paper or blog post.

 

Office hours for this course:
Please email to make an appointment magajm@uw.edu

Note:
Classes are offered at the EScience Studio, there is no virtual participation. However, tutoring/office hours can be virtually.

This 2023 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 eScience and Evans School at UW, and to the work he develops at GI3P.