Global Certificate in Fisheries Data & Predictive Analytics
-- ViewingNowThe Global Certificate in Fisheries Data & Predictive Analytics is a comprehensive course designed to equip learners with essential skills in data analysis and predictive modeling for the fisheries industry. With the increasing demand for data-driven decision-making in fisheries management, this course is crucial for professionals seeking to advance their careers.
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GBP £ 140
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โข Fisheries Data Management: An overview of best practices for collecting, organizing, and storing fisheries data. This unit will cover data types, sources, and common challenges in fisheries data management.
โข Data Cleaning & Preprocessing: Techniques for cleaning and preparing fisheries data for analysis, including data imputation, outlier detection, and normalization.
โข Exploratory Data Analysis (EDA): An introduction to EDA techniques for fisheries data, including visualization and statistical analysis.
โข Predictive Analytics in Fisheries: An exploration of predictive modeling techniques for fisheries, including regression analysis, time series forecasting, and machine learning algorithms.
โข Stock Assessment Models: A deep dive into stock assessment models, including their assumptions, strengths, and limitations. This unit will cover single-species and multispecies models, as well as their applications in fisheries management.
โข Spatial Analysis in Fisheries: An overview of spatial analysis techniques in fisheries, including geographic information systems (GIS), spatial autocorrelation, and spatial interpolation.
โข Machine Learning for Fisheries: An exploration of machine learning techniques for fisheries, including supervised and unsupervised learning algorithms, and their applications in fisheries management.
โข Data Visualization in Fisheries: Techniques for visualizing fisheries data, including data storytelling, interactive visualizations, and data dashboards.
โข Ethics in Fisheries Data & Analytics: A discussion of ethical considerations in fisheries data and analytics, including data privacy, bias, and transparency.
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