Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** the food and agriculture industry…

Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** the food and agriculture industry continues to advance, reaching new technological milestones that were once the topic of science fiction. While these advancements should be celebrated, they have also created an emerging problem in workforce training. Digital technologies are only useful if a worker understands how to use them and how to interpret the data they generate. However, curricular topics such as data analytics, geospatial software, and remote sensing have traditionally been taught as upper level courses at four-year institutions. This lack of access to curriculum has created a digital divide in our workforce, placing both the emerging technical workforce and the workforce in need of retraining at a significant disadvantage. The overall goal of this project is to remove the curricular barrier to creating a technology- and data-savvy workforce. To accomplish this task, we propose a three-pronged approach: (1) the creation of online and open-source training materials which maybe viewed independently or incorporated into current courses at technical colleges, (2) the availability of regional face-to-face training workshops which cover the data access, analysis, and decision-making concepts which are most integral to the food and agriculture industry, and (3) the piloting of two new industry-aligned credentialing programs in data analysis and geospatial information systems (GIS). At the conclusion of this work, IT is expected that not only will we have created and piloted a sustainable workforce training platform, but also trained a minimum of 250 workshop participants and 32 industry-credentialed students in emerging data and technology applications.