Items related to Applied Data Science in FinTech: Models, Tools, and...
Synopsis
This textbook offers a comprehensive introduction to data science and financial technology, with a focus on advanced tools, data modeling, and their applications in FinTech. Adopting an inquiry-based approach, it integrates detailed case studies, clear definitions of financial terms, and practical examples to guide readers through core concepts and methods.
Step-by-step illustrations demonstrate how programs are developed, making the material accessible for students. Dedicated chapters explore cutting-edge applications such as AdviceTech, AgTech, PropTech, chatbots, and sentiment analytics. To support hands-on learning, the book also provides sample code and data sets, enabling readers to experiment, practice, and ultimately design their own programs.
Designed for those with a basic foundation in programming, this book is an ideal companion for applying data science techniques to financial and technological contexts. It is particularly valuable for postgraduate and advanced students in FinTech, Business Analytics, and Data Science programs.
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About the Author
Juraj Hric is Co-Founder and Chief Executive Officer at Zyanza Technologies. He is a course convenor for banking, finance and financial technology modules at the University of New South Wales, Australia.
Yiping Lin is Co-Founder of Alt Data Tech, a leading provider of alternative data. He is also the director of undergraduate and postgraduate FinTech programs at the University of New South Wales, Australia.
"About this title" may belong to another edition of this title.
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Applied Data Science in FinTech (Hardcover)
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Taylor & Francis Ltd, London, 2026
ISBN 10: 1032762586
ISBN 13: 9781032762586
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Hardcover. Condition: new. Hardcover. This textbook offers a comprehensive introduction to data science and financial technology, with a focus on advanced tools, data modeling, and their applications in FinTech. Adopting an inquiry-based approach, it integrates detailed case studies, clear definitions of financial terms, and practical examples to guide readers through core concepts and methods.Step-by-step illustrations demonstrate how programs are developed, making the material accessible for students. Dedicated chapters explore cutting-edge applications such as AdviceTech, AgTech, PropTech, chatbots, and sentiment analytics. To support hands-on learning, the book also provides sample code and data sets, enabling readers to experiment, practice, and ultimately design their own programs.Designed for those with a basic foundation in programming, this book is an ideal companion for applying data science techniques to financial and technological contexts. It is particularly valuable for postgraduate and advanced students in FinTech, Business Analytics, and Data Science programs. This text offers a comprehensive introduction to data science and financial technology, with a focus on advanced tools, data modeling, and their applications in FinTech. Adopting an inquiry-based approach, it integrates detailed case studies, clear definitions of financial terms, and practical examples to guide readers through core concepts. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781032762586
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Applied Data Science in FinTech (Hardcover)
Published by
Taylor & Francis Ltd, London, 2026
ISBN 10: 1032762586
ISBN 13: 9781032762586
New
Hardcover
Seller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. This textbook offers a comprehensive introduction to data science and financial technology, with a focus on advanced tools, data modeling, and their applications in FinTech. Adopting an inquiry-based approach, it integrates detailed case studies, clear definitions of financial terms, and practical examples to guide readers through core concepts and methods.Step-by-step illustrations demonstrate how programs are developed, making the material accessible for students. Dedicated chapters explore cutting-edge applications such as AdviceTech, AgTech, PropTech, chatbots, and sentiment analytics. To support hands-on learning, the book also provides sample code and data sets, enabling readers to experiment, practice, and ultimately design their own programs.Designed for those with a basic foundation in programming, this book is an ideal companion for applying data science techniques to financial and technological contexts. It is particularly valuable for postgraduate and advanced students in FinTech, Business Analytics, and Data Science programs. This text offers a comprehensive introduction to data science and financial technology, with a focus on advanced tools, data modeling, and their applications in FinTech. Adopting an inquiry-based approach, it integrates detailed case studies, clear definitions of financial terms, and practical examples to guide readers through core concepts. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781032762586
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Applied Data Science in FinTech (Hardcover)
Published by
Taylor & Francis Ltd, London, 2026
ISBN 10: 1032762586
ISBN 13: 9781032762586
New
Hardcover
Seller: AussieBookSeller, Truganina, VIC, Australia
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Hardcover. Condition: new. Hardcover. This textbook offers a comprehensive introduction to data science and financial technology, with a focus on advanced tools, data modeling, and their applications in FinTech. Adopting an inquiry-based approach, it integrates detailed case studies, clear definitions of financial terms, and practical examples to guide readers through core concepts and methods.Step-by-step illustrations demonstrate how programs are developed, making the material accessible for students. Dedicated chapters explore cutting-edge applications such as AdviceTech, AgTech, PropTech, chatbots, and sentiment analytics. To support hands-on learning, the book also provides sample code and data sets, enabling readers to experiment, practice, and ultimately design their own programs.Designed for those with a basic foundation in programming, this book is an ideal companion for applying data science techniques to financial and technological contexts. It is particularly valuable for postgraduate and advanced students in FinTech, Business Analytics, and Data Science programs. This text offers a comprehensive introduction to data science and financial technology, with a focus on advanced tools, data modeling, and their applications in FinTech. Adopting an inquiry-based approach, it integrates detailed case studies, clear definitions of financial terms, and practical examples to guide readers through core concepts. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781032762586
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