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Artificial Intelligence in Mathematics, Statistics & Physics
Artificial intelligence increasingly depends on mathematical rigor, statistical reasoning and multidisciplinary scientific foundations. Explore textbooks that examine causal reasoning, mathematical tools and scientific applications of AI across mathematics, statistics and physics.
Mathematics for Artificial Intelligence Provides the essential mathematics underpinning AI and machine learning, covering calculus, linear algebra, probability and more, with examples connected to AI applications. Suitable courses: Mathematics for AI, machine learning foundations, applied mathematics, quantitative methods for data science (Upper undergraduate / postgraduate) |
Artificial Intelligence and Causal Inference Examines the relationship between AI and causal inference, addressing reasoning, intervention, counterfactuals and deep learning methods applied to causal analysis and AI problems. Suitable courses: AI, data science, causal inference, statistics, genomics, bioinformatics, precision medicine (Graduate / researcher) |
Introduction to Multidisciplinary Science with Artificial Intelligence Introduces broad scientific concepts from geodesy and heat transfer to quantum entanglement and spectroscopy, and illustrates their interdisciplinary applications with analytical and computational (MATLAB) problems. Suitable courses: Multidisciplinary science & AI, computational physics, physical science foundations, mathematical modelling in science (Undergraduate / postgraduate) |
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