Andrei Kirilenko (14 results)

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Paperback. Condition: 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.

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Paperback. Condition: Brand New. 534 pages. 9.26x6.11x0.98 inches. In Stock.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Taschenbuch. Condition: 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.

Condition: new. Questo è un articolo print on demand.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 520 pp. Englisch.

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 536 pp. Englisch.