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The Data Science Upskilling program successfully enhanced data science skills and confidence among public health professionals at the Centers for Disease Control and Prevention (CDC). This initiative demonstrates a scalable model for improving data literacy in public health organizations.

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Area of Science:

  • Public Health
  • Data Science Education
  • Workforce Development

Background:

  • Effective public health decision-making relies on data, necessitating data science skills among professionals.
  • A gap exists in data science competencies within public health, including at the Centers for Disease Control and Prevention (CDC).

Purpose of the Study:

  • To evaluate the impact of the Data Science Upskilling (DSU) program on enhancing data science literacy and skills among CDC staff and fellows.

Main Methods:

  • The DSU program is a team-based, project-driven, on-the-job applied learning initiative.
  • Learners utilized curated resources to advance their specific CDC projects within interdisciplinary teams.
  • Program expansion tracked from 31 learners in 2019-2020 to 143 learners in 2022-2023.

Main Results:

  • 100% of 2022-2023 survey respondents reported increased data science knowledge.
  • 90% reported improved data science skills, 93% improved confidence in data-driven decision-making, and 96% improved ability to perform data science work benefiting the CDC.

Conclusions:

  • The Data Science Upskilling program is an effective, inclusive, and innovative approach to boosting data science literacy at the CDC.
  • The DSU program's success suggests its potential as a transferable model for upskilling in other organizations.