Professional Certificate in Data Science for Coastal Applications
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⢠Fundamentals of Data Science → Study of basic concepts, principles, and techniques in data science, including data collection, cleaning, and pre-processing.
⢠Coastal Processes → Examination of physical, chemical, and biological processes occurring in coastal environments, emphasizing the importance of spatial and temporal scales.
⢠Statistical Analysis for Coastal Applications → Application of statistical methods and tools to analyze coastal data, including descriptive and inferential statistics, probability distributions, and hypothesis testing.
⢠Geographic Information Systems (GIS) → Introduction to GIS technology, data models, and techniques for managing, analyzing, and visualizing spatial data relevant to coastal applications.
⢠Machine Learning for Coastal Processes → Study of machine learning methods and techniques for predicting and modeling coastal processes, including regression, classification, clustering, and neural networks.
⢠Remote Sensing for Coastal Monitoring → Exploration of remote sensing technologies and techniques for monitoring coastal environments, including satellite and airborne sensors, image processing, and feature extraction.
⢠Data Visualization & Communication → Development of skills in creating effective visualizations of coastal data, conveying complex information in a clear and concise manner, and communicating results to stakeholders.
⢠Coastal Modeling & Simulation → Application of numerical models and simulation techniques to predict coastal processes and phenomena, including waves, tides, sediment transport, and water quality.
⢠Big Data Analytics for Coastal Management → Examination of big data technologies and tools for managing, processing, and analyzing large and complex coastal datasets, including distributed computing and data mining.
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