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Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviours, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionise the future of chemistry. Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and current developments in the field, giving readers insight into how these tools can be harnessed to enhance their own work. Volume 1 explores the fundamental knowledge and current methods being used to apply AI across a whole host of chemistry applications. Part 1 provides foundational information on AI in chemistry, with an introduction to the field and guidance on database usage and statistical analysis to help support newcomers to the field. Part 2 then goes on to discuss approaches currently used to address problems in broad areas such as computational and theoretical chemistry; materials, synthetic and medicinal chemistry; crystallography, analytical chemistry, and spectroscopy. Finally, potential future trends in the field are discussed. Drawing on the knowledge of its expert team of global contributors, Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications is a fascinating insight into this rapidly developing field and a great resource for all those interested in exploring the opportunities afforded by the intersection of chemistry and AI in their own work. Provides an accessible introduction to the current state and future possibilities for AI in chemistryExplores how computational chemistry methods and approaches can both enhance and be enhanced by AIHighlights the interdisciplinary, broad applicability of AI tools across a wide range of chemistry fields