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Curriculum

The Graduate Certificate in Agricultural Data Science is targeted toward enrolled graduate students in the agri-food sciences at the University of Georgia and aimed at producing graduates capable of bridging the gap between the generation, analysis, and interpretation of structured and unstructured agricultural data. The curriculum is highly interdisciplinary and encompasses 16 credit hours in the following areas:

  • Area 1: Agricultural Data Science Core (6 credits): Two required courses covering the foundations in descriptive and predictive analytics in the agri-food sciences and providing context for and integration among more specialized data science elective courses.
  • Area 2: Analytical Foundations (3 credits): More specialized elective courses in the foundations of data science: programming, data management, statistics, econometrics, and/or data mining.
  • Area 3: Analytical Applications (at least 6 credits): Elective courses from a range of applications including precision agriculture, geographic information science, imaging and sensing, experimental statistics, bioinformatics, and consumer analytics, among others.
  • Area 4: Seminar in Agricultural Data Science (1 credit): Capstone seminar course featuring UGA and external speakers highlighting diverse applications in agricultural analytics.

Inventory of required and elective Agricultural Data Science courses (last updated 2 November 2018)