Executive Development Programme in Data-Driven Fisheries Innovations
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⢠Data Analysis for Fisheries Management: This unit will cover the fundamentals of data analysis and its application in fisheries management. Topics include data collection, cleaning, and preprocessing, as well as statistical analysis and visualization techniques.
⢠Fisheries Data Management Systems: This unit will explore various data management systems used in the fisheries industry, including databases, data warehouses, and data lakes. Students will learn how to design, implement, and maintain these systems to support data-driven decision-making.
⢠Machine Learning for Fisheries: This unit will introduce students to machine learning techniques and their application in fisheries. Topics include predictive modeling, clustering, and classification, as well as natural language processing and computer vision for fisheries data analysis.
⢠Satellite Remote Sensing for Fisheries: This unit will cover the use of satellite remote sensing for fisheries management, including the collection and analysis of oceanographic data, habitat mapping, and fisheries monitoring and surveillance.
⢠Internet of Things (IoT) in Fisheries: This unit will explore the use of IoT devices in fisheries, including sensor networks, drones, and underwater vehicles. Students will learn how to design, deploy, and manage these systems to support data-driven fisheries management.
⢠Data Visualization and Communication: This unit will cover best practices for data visualization and communication in the fisheries industry. Topics include visual design principles, data storytelling, and effective communication strategies for data-driven decision-making.
⢠Ethics and Data Privacy in Fisheries: This unit will explore the ethical and privacy considerations surrounding the use of data in fisheries. Topics include data privacy laws and regulations, ethical data collection and use, and the responsible use of data in fisheries management.
⢠Data-Driven Innovation in Fisheries: This unit will cover best practices for driving innovation in fisheries through data-driven decision-making. Topics include identifying and prioritizing innovation opportunities, designing and implementing data-driven interventions, and measuring and evaluating the impact of innovation efforts.
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