Data Science Applications in Agriculture

3.0 credits · Undergraduate

This course provides an experience in challenge-based learning, focusing on data-driven problems in the agricultural sector. Students work in collaborative teams, engaging with farmers and industry stakeholders to understand real-world challenges and develop innovative solutions. Students will use various digital tools essential for modern data science. Key topics include data governance, privacy, collection methods, storage solutions, processing techniques, and advanced visualization. Students will also learn data modeling and effective data presentation. Project management is a core component, teaching students to manage projects, meet deadlines, and deliver timely results. The course emphasizes teamwork, communication, and collaboration, preparing students for diverse and dynamic environments. This course is ideal for those interested in applying data science to real-world problems and making a tangible impact in agriculture.