Digital Agriculture (MSDA) 

Core Courses (12 Units)

MSDA 500: Principles of Digital Agriculture
This course introduces the fundamental concepts, frameworks, and applications that define the emerging field of digital agriculture. It examines the integration of digital technologies—such as precision farming tools, data-driven management systems, and smart agricultural platforms—into modern agricultural practices. Emphasis is placed on understanding the relationships among technology, sustainability, and productivity, and on evaluating how digital innovations transform agricultural value chains, decision-making, and food security. Students will gain a comprehensive overview of the digital transformation of agriculture within global and regional contexts.

MSDA 501: Agricultural Data Analytics and Decision Support Systems
This course provides an in-depth study of data analytics as applied to agriculture and agribusiness. It focuses on data collection, management, analysis, and interpretation for evidence-based decision-making. Students will learn to use data-driven methodologies to optimize crop yield, resource allocation, and farm management practices. The course also explores the design and use of decision support systems (DSS) that integrate real-time data, predictive models, and information visualization to enhance agricultural planning and sustainability.

MSDA 502: Remote Sensing, and Drone Application in Agriculture
This course explores the principles and applications of remote sensing technologies and unmanned aerial systems (UAS) in agricultural contexts. Topics include geospatial data acquisition, image processing, vegetation monitoring, soil analysis, and crop assessment. Students will develop practical skills in using satellite imagery and drone-based technologies to evaluate crop health, detect stress conditions, and support precision agriculture initiatives. The course highlights how spatial data enhances agricultural productivity, environmental monitoring, and resource conservation.

MSDA 503: Sustainable and Climate-Smart Agriculture
This course examines strategies and technologies that promote environmental sustainability and resilience in agricultural systems. It covers climate-smart approaches, including adaptive crop management, soil conservation, and the integration of renewable technologies in farming practices. Students will analyze global frameworks and case studies addressing climate change adaptation, mitigation, and food security. Emphasis is placed on the application of digital tools to support sustainable land use, ecosystem preservation, and responsible agricultural innovation.

Concentration (18 units)
MSDA 601: IoT and Automation in Agriculture
This course studies the role of the Internet of Things (IoT), sensors, and automation technologies in transforming agricultural operations. It explores smart systems for monitoring soil moisture, crop growth, livestock health, and environmental conditions. Students will examine the design and implementation of automated systems such as precision planting, irrigation control, and robotic harvesting. The course underscores the importance of interoperability, data communication, and real-time decision-making in achieving efficiency and sustainability in agriculture.

MSDA 602: Artificial Intelligence and Machine Learning Agri-Systems
This course introduces the application of artificial intelligence (AI) and machine learning (ML) techniques in solving complex agricultural problems. It focuses on predictive modeling, image classification, yield forecasting, and pest or disease detection. Students will explore algorithmic approaches to data processing and develop an understanding of how AI-driven systems contribute to precision agriculture, resource optimization, and smart farm management. Ethical and policy considerations in the use of AI in agriculture are also discussed.

MSDA 603: Big Data Management and Cloud Computing in Agriculture
This course provides a comprehensive overview of big data technologies and cloud-based solutions supporting agricultural systems. Students will examine frameworks for managing large and diverse datasets generated from sensors, satellites, and field operations. Topics include cloud storage, distributed computing, data integration, and security in agricultural contexts. The course emphasizes how big data and cloud computing enable real-time analytics, predictive modeling, and collaborative research across agricultural networks.

MSDA 604: Digital Agribusiness and Supply Chain Management
This course explores the digital transformation of agribusiness and the integration of information systems within agricultural supply chains. It examines e-commerce platforms, blockchain traceability, logistics optimization, and digital marketing strategies for agricultural products. Students will analyze case studies demonstrating how digital tools enhance efficiency, transparency, and value creation in global and local food systems. The course prepares learners to manage technology-enabled agribusiness ventures and sustainable value chains.

MSDA 605: Smart Irrigation and Water Resource Management
This course addresses the design and implementation of smart irrigation systems and sustainable water management strategies in agriculture. It covers precision irrigation technologies, hydrological modeling, and sensor-based monitoring of water usage. Students will learn to apply data-driven approaches to optimize irrigation scheduling, reduce water waste, and improve crop productivity under variable climatic conditions. The course also discusses policy frameworks and environmental considerations in agricultural water management.

MSDA 606: Agricultural Policy, Innovation, and Entrepreneurship
This course examines the intersection of agricultural policy, technological innovation, and entrepreneurship within the digital agriculture landscape. It provides students with an understanding of policy instruments that support agricultural innovation, rural development, and digital transformation. Emphasis is placed on the development of entrepreneurial mindsets and business models for agri-tech ventures. Students will evaluate case studies of policy reforms, innovation ecosystems, and startup success stories contributing to sustainable agricultural advancement.

Thesis Requirements: (6 units)
MSDA 699: Thesis in Digital Agriculture
This course represents the culminating scholarly requirement for the Master of Science in Digital Agriculture program. It provides students the opportunity to conduct independent, original research that contributes to the body of knowledge in digital and sustainable agriculture. Under the guidance of a faculty adviser, students will identify a research problem, review relevant literature, design and implement appropriate methodologies, analyze data, and present results that demonstrate critical thinking, academic rigor, and practical relevance.

The thesis should address contemporary issues in digital agriculture such as precision farming, agricultural data analytics, climate-smart systems, or technology-driven solutions for agricultural productivity and sustainability. The final manuscript must meet graduate-level standards of research design, writing, and ethical practice. Successful completion of the thesis requires an oral defense before a panel of faculty evaluators.