COURSE OVERVIEW

 

This practical and highly-interactive course includes various practical sessions and exercises. Theory learnt will be applied using our state-of-the-art simulators. 

This course is designed to provide participants with a detailed and up-to-date overview of Enabling Decision Making with Data. It covers the importance of data-driven decision-making in agriculture and food safety; the various types of data in agriculture and food; the decision-making process and the role of analytics in decision-making; the data storage platforms, data collection ethics and privacy laws and regulations in agriculture; the data collection techniques, data quality and validation and data management and storage; and the data integration, handling missing and inconsistent data and preparing metadata and documentation. 

During this interactive course, participants will learn the data analysis, detecting patterns and trends and identifying anomalies; the statistical analysis techniques covering basic statistical methods, hypothesis testing and correlation and regression analysis; the data visualization best practices, predictive analytics and interpreting analysis results; the what-if analysis and risk assessment and management; the use of data for regulatory decisions, real-time decision-making and data in crisis management; measuring the impact of data-driven decisions, collecting feedback for improvement and iterative decision-making; the implementation plan, assigning roles and responsibilities and monitoring and evaluating plans; the collaborative decision-making and the emerging trends in agriculture and data; and the challenges in adoption and how to overcome them.