Applications of Machine Learning Techniques in Sustainable Technologies (AMLST-2024)

24 Jan 2024   -   28 Jan 2024
Electrical Engineering
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This short-term course is designed to provide participants with a comprehensive understanding of how advanced machine learning techniques can be harnessed to address critical challenges in the realm of sustainability. This course offers a rigorous academic exploration of the complexities, strengths, and benefits of utilizing Machine Learning in sustainable technology applications (like as Electric Mobility, Energy Management in Renewable Sources, Cyber-Physical System, Health Monitoring of Batteries, Waste Management, Biomedical Signal Processing, Agricultural Yield Prediction etc.). Participants will grapple with the intricacies of environmental data, honing their skills in preprocessing and modeling to derive actionable insights from complex datasets. While navigating the ethical dimensions of AI, they will learn to mitigate biases and ensure fairness in algorithmic decision-making. The course empowers participants with the knowledge and practical skills required to optimize renewable energy systems, predict resource consumption trends, and enhance resource allocation efficiency, ultimately contributing to a more sustainable and responsible technological landscape. Through a blend of theoretical insights and hands-on applications, participants emerge equipped to lead in the development and implementation of eco-conscious technologies. The course is applicable for students, researchers, and engineering professionals who want to do research in fast growing and emerging renewable energy technology.