This book is designed as a foundational textbook for upper-level undergraduate and graduate students from non-technical fields who want to acquire a basic understanding of data science and learn practical skills in data analysis. It distinguishes itself by combining theoretical knowledge with practical applications, bridged through extensive Python programming exercises. To accommodate social scientists' needs, the book emphasizes the analysis of textual data, especially those acquired from surveys and social media. For those without prior programming experience, the book provides instruction on using an AI-assisted Python programming tool, following the learn-by-doing methodology of acquiring new skills through experience. The overall learning goal of the book is to develop a conceptual understanding of data mining as well as the technical skills necessary for real-world data analysis.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Andrei Kirilenko has a degree in applied mathematics and a Ph.D. in computer science. He started his career developing computer models for evaluating climate change impacts on the natural environment and agriculture. Gradually, his teaching and research interests have shifted toward quantitative social science research. Since 2015, he has held the position of Associate Professor at the Department of Tourism, Hospitality, and Event Management at the University of Florida, USA, teaching courses on data mining for social sciences, Geographical Information Systems, statistics, and research methods. His research is centered on social media analysis, sustainability, and biodiversity. Dr. Kirilenko has served as an expert in the global assessments of the Intergovernmental Panel on Climate Change (IPCC) and the United Nations Environmental Program (UNEP) Global Environmental Assessments.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : new. Paperback. This book is designed as a foundational textbook for upper-level undergraduate and graduate students from non-technical fields who want to acquire a basic understanding of data science and learn practical skills in data analysis. It distinguishes itself by combining theoretical knowledge with practical applications, bridged through extensive Python programming exercises. To accommodate social scientists' needs, the book emphasizes the analysis of textual data, especially those acquired from surveys and social media. For those without prior programming experience, the book provides instruction on using an AI-assisted Python programming tool, following the learn-by-doing methodology of acquiring new skills through experience. The overall learning goal of the book is to develop a conceptual understanding of data mining as well as the technical skills necessary for real-world data analysis. mso-bidi-language: AR-SA;">This book is designed as a foundational textbook for upper-level undergraduate and graduate students from non-technical fields who want to acquire a basic understanding of data science and learn practical skills in data analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783031896880
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Taschenbuch. Etat : Neu. Practical Data Mining with AI for Social Scientists | Andrei P. Kirilenko | Taschenbuch | Springer Texts in Social Sciences | xiv | Englisch | 2026 | Springer | EAN 9783031896880 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 134444526
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