Data Literacy

PhD Plus Data Literacy core module is best suited for PhD students in middle and advanced years, and all Postdoctoral Scholars (collectively called trainees) who are interested in research careers, careers in data science, data management, data storytelling, and related careers. This module is developed and offered through collaboration between PhD+ and the UVA Library’s Research Data Services, Data Services at the Health Sciences Library, and UVA Research Computing Group.

LEARNING GOALS

  • Obtain knowledge of data science-related career options after PhD and Postdoc training
  • Gain awareness of the broad PhD skills that are well-suited for data science-related careers
  • Access opportunity to cultivate a community of data science professionals and organizations in the University, Charlottesville community and beyond
  • Develop foundational skills and experience in using languages such as R and Python for data wrangling, analysis, visualization, and more.

RECOMMENDED PRIOR TRAINING

Data Literacy

 

For optimal learning experience and outcomes, we recommend participation in PhD Plus Career Design prior to this module. 

A student-centered engagement strategy for career education and professional development in Data Literacy (also applicable to all PhD Plus career training core modules). For details, please refer to program philosophy and attend PhD Plus Career Design. Click on menu links for Research, Community and Skills to determine specific engagement strategy

 

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Research

 

Are you curious about data-related careers after PhD? Learn about careers that leverage analytics, management, visualization and storytelling of data in academia, industry, non-profit and government. 

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Community

 

To learn about data-related careers, you should cultivate a professional community and connect with professionals in these fields.

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Skills Series

 

PhD Plus offers two skills series: R in Spring and Python in Fall. Click here for details on learning objectives, topics, and dates.

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Experience

 

Here, you can learn about experiential learning opportunities for data literacy and data science, and stories of PhD student participants.