Undergraduate Certificate in AI-Based Harmful Algal Bloom Monitoring

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The Undergraduate Certificate in AI-Based Harmful Algal Bloom Monitoring is a cutting-edge course that combines artificial intelligence (AI) and remote sensing to monitor harmful algal blooms (HABs). This certificate is critical in addressing the growing environmental and public health concerns caused by HABs.

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ใ“ใฎใ‚ณใƒผใ‚นใซใคใ„ใฆ

With a projected 31% increase in water monitoring jobs by 2028, this course prepares learners for in-demand careers in environmental monitoring and protection. Through this course, learners acquire essential skills in AI, remote sensing, data analysis, and environmental monitoring. They gain hands-on experience using AI tools and techniques to analyze remote sensing data and detect HABs. These skills are highly valued in various industries, including environmental consulting, government agencies, and non-profit organizations. By earning this certificate, learners demonstrate their expertise in AI-based HAB monitoring, setting them apart in a competitive job market. They are equipped with the skills and knowledge to develop and implement AI-based solutions for environmental monitoring, making a positive impact on the environment and public health.

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ใ‚ณใƒผใ‚น่ฉณ็ดฐ

โ€ข Introduction to AI & Machine Learning in Harmful Algal Bloom (HAB) Monitoring
โ€ข Understanding HABs: Types, Causes, and Impacts
โ€ข Data Collection Techniques for HAB Monitoring
โ€ข AI-Based HAB Detection and Prediction Models
โ€ข Image Processing and Computer Vision for HAB Cell Counting
โ€ข Satellite Remote Sensing for HAB Monitoring
โ€ข Real-time HAB Monitoring System Development
โ€ข Ethical and Societal Implications of AI in HAB Monitoring
โ€ข Evaluation and Optimization of AI-Based HAB Monitoring Systems

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ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
UNDERGRADUATE CERTIFICATE IN AI-BASED HARMFUL ALGAL BLOOM MONITORING
ใซๆŽˆไธŽใ•ใ‚Œใพใ™
ๅญฆ็ฟ’่€…ๅ
ใงใƒ—ใƒญใ‚ฐใƒฉใƒ ใ‚’ๅฎŒไบ†ใ—ใŸไบบ
London School of International Business (LSIB)
ๆŽˆไธŽๆ—ฅ
05 May 2025
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