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Exploring university mathematics with Python

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Exploring university mathematics with Python/ by Siri Chongchitnan.
作者:	Chongchitnan, Siri.
出版者:	Cham :Springer Nature Switzerland : : 2023.,
面頁冊數:	xiii, 514 p. :illustrations (chiefly color), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Probability Theory. -
電子資源:	https://doi.org/10.1007/978-3-031-46270-2
ISBN:	9783031462702

Exploring university mathematics with Python
Chongchitnan, Siri.

Exploring university mathematics with Python[electronic resource] /by Siri Chongchitnan. - Cham :Springer Nature Switzerland :2023. - xiii, 514 p. :illustrations (chiefly color), digital ;24 cm.

1 Analysis -- 2 Calculus -- 3 Vector Calculus and Geometry -- 4 Differential Equations and Dynamical Systems -- 5 Linear Algebra -- 6 Abstract Algebra and Number Theory -- 7 Probability -- 8 Statistics -- Appendix A: Python 101.

This book provides a unique tour of university mathematics with the help of Python. Written in the spirit of mathematical exploration and investigation, the book enables students to utilise Python to enrich their understanding of mathematics through: Calculation: performing complex calculations and numerical simulations instantly Visualisation: demonstrating key theorems with graphs, interactive plots and animations Extension: using numerical findings as inspiration for making deeper, more general conjectures. This book is for all learners of mathematics, with the primary audience being mathematics undergraduates who are curious to see how Python can enhance their understanding of core university material. The topics chosen represent a mathematical overview of what students typically study in the first and second years at university, namely analysis, calculus, vector calculus and geometry, differential equations and dynamical systems, linear algebra, abstract algebra and number theory, probability and statistics. As such, it can also serve as a preview of university mathematics for high-school students. The prerequisites for reading the book are a familiarity with standard A-Level mathematics (or equivalent senior high-school curricula) and a willingness to learn programming. For mathematics lecturers and teachers, this book is a useful resource on how Python can be seamlessly incorporated into the mathematics syllabus, assuming only basic knowledge of programming.

ISBN: 9783031462702

Standard No.: 10.1007/978-3-031-46270-2doiSubjects--Topical Terms:

1366244
Probability Theory.

LC Class. No.: QA37.3

Dewey Class. No.: 510

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505 0 $a 1 Analysis -- 2 Calculus -- 3 Vector Calculus and Geometry -- 4 Differential Equations and Dynamical Systems -- 5 Linear Algebra -- 6 Abstract Algebra and Number Theory -- 7 Probability -- 8 Statistics -- Appendix A: Python 101.
520 $a This book provides a unique tour of university mathematics with the help of Python. Written in the spirit of mathematical exploration and investigation, the book enables students to utilise Python to enrich their understanding of mathematics through: Calculation: performing complex calculations and numerical simulations instantly Visualisation: demonstrating key theorems with graphs, interactive plots and animations Extension: using numerical findings as inspiration for making deeper, more general conjectures. This book is for all learners of mathematics, with the primary audience being mathematics undergraduates who are curious to see how Python can enhance their understanding of core university material. The topics chosen represent a mathematical overview of what students typically study in the first and second years at university, namely analysis, calculus, vector calculus and geometry, differential equations and dynamical systems, linear algebra, abstract algebra and number theory, probability and statistics. As such, it can also serve as a preview of university mathematics for high-school students. The prerequisites for reading the book are a familiarity with standard A-Level mathematics (or equivalent senior high-school curricula) and a willingness to learn programming. For mathematics lecturers and teachers, this book is a useful resource on how Python can be seamlessly incorporated into the mathematics syllabus, assuming only basic knowledge of programming.
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