Advanced AI & LLM Applications in Sustainability
This advanced course explores the integration of artificial intelligence (AI) and large language models (LLMs) to address critical sustainability challenges. Participants will delve into cutting-edge AI techniques, such as deep learning, reinforcement learning, and predictive analytics, and their applications in climate modeling, energy systems, sustainable agriculture, waste management, and supply chains. The course also emphasizes leveraging LLMs for environmental data analysis, sustainability reporting, and policy development. Through hands-on projects and real-world case studies, learners will gain the skills needed to design innovative AI-driven solutions for global sustainability efforts.
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Course Duration:
36 hours
Level:
Advanced
Course Objectives
Master advanced AI techniques and their applications in sustainability, including climate modeling, energy optimization, and sustainable agriculture.
Learn to apply LLMs for environmental data analysis, sustainability reporting, and policy recommendations.
Understand the role of AI in optimizing sustainable supply chains and waste management systems.
Analyse the ethical, legal, and regulatory implications of AI in sustainability contexts.
Design and implement scalable AI-driven solutions to address complex sustainability challenges.
Prerequisites
Strong understanding of machine learning and deep learning fundamentals.
Familiarity with natural language processing (NLP) and LLM concepts (e.g., GPT, BERT).
Proficiency in programming languages such as Python, including AI/ML frameworks (e.g., TensorFlow, PyTorch).
Basic knowledge of sustainability concepts and environmental science.
Prior experience in AI-related projects or equivalent professional expertise is recommended.
