Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
EUR 102,12
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierHardback. Etat : New. New copy - Usually dispatched within 4 working days. 453.
EUR 107,52
Autre deviseQuantité disponible : 3 disponible(s)
Ajouter au panierEtat : New.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 100,46
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : As New. Unread book in perfect condition.
EUR 113,05
Autre deviseQuantité disponible : 4 disponible(s)
Ajouter au panierEtat : New. 1st edition NO-PA16APR2015-KAP.
EUR 57,43
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : good. Has a sturdy binding with some shelf wear. May have some markings or highlighting. Used copies may not include access codes or Cd's. Slight bending may be present.
EUR 118,60
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. In.
Edité par Taylor & Francis Ltd, London, 2024
ISBN 10 : 1032278366 ISBN 13 : 9781032278360
Langue: anglais
Vendeur : AussieBookSeller, Truganina, VIC, Australie
EUR 95,68
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : new. Hardcover. This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Both analytical and computational examples are integrated from its start. Each chapter concludes with a set of problems designed to help students hone their skills in mathematical techniques, computer programming, and numerical analysis. The book places less emphasis on mathematical proofs, and more emphasis on how to use computers for both symbolic and numerical calculations. It contains 182 extensively documented coding examples, based on topics that students will encounter in their advanced courses in Mechanics, Electronics, Optics, Electromagnetism, Quantum Mechanics etc.An introductory chapter gives students a crash course in Python programming and the most often used libraries (SymPy, NumPy, SciPy, Matplotlib). This is followed by chapters dedicated to differentiation, integration, vectors and multiple integration techniques. The next group of chapters covers complex numbers, matrices, vector analysis and vector spaces. Extensive chapters cover ordinary and partial differential equations, followed by chapters on nonlinear systems and on the analysis of experimental data using linear and nonlinear regression techniques, Fourier transforms, binomial and Gaussian distributions. The book is accompanied by a dedicated GitHub website, which contains all codes from the book in the form of ready to run Jupyter notebooks. A detailed solutions manual is also available for instructors using the textbook in their courses.Key Features:A unique teaching approach which merges mathematical methods and the Python programming skills which physicists and engineering students need in their coursesUses examples and models from physical and engineering systems, to motivate the mathematics being taughtStudents learn to solve scientific problems in three different ways: traditional pen-and-paper methods, using scientific numerical techniques with NumPy and SciPy, and using Symbolic Python (SymPy). This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 112,88
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 114,98
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 129,72
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Taylor & Francis Ltd, London, 2024
ISBN 10 : 1032278366 ISBN 13 : 9781032278360
Langue: anglais
Vendeur : CitiRetail, Stevenage, Royaume-Uni
EUR 125,15
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : new. Hardcover. This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Both analytical and computational examples are integrated from its start. Each chapter concludes with a set of problems designed to help students hone their skills in mathematical techniques, computer programming, and numerical analysis. The book places less emphasis on mathematical proofs, and more emphasis on how to use computers for both symbolic and numerical calculations. It contains 182 extensively documented coding examples, based on topics that students will encounter in their advanced courses in Mechanics, Electronics, Optics, Electromagnetism, Quantum Mechanics etc.An introductory chapter gives students a crash course in Python programming and the most often used libraries (SymPy, NumPy, SciPy, Matplotlib). This is followed by chapters dedicated to differentiation, integration, vectors and multiple integration techniques. The next group of chapters covers complex numbers, matrices, vector analysis and vector spaces. Extensive chapters cover ordinary and partial differential equations, followed by chapters on nonlinear systems and on the analysis of experimental data using linear and nonlinear regression techniques, Fourier transforms, binomial and Gaussian distributions. The book is accompanied by a dedicated GitHub website, which contains all codes from the book in the form of ready to run Jupyter notebooks. A detailed solutions manual is also available for instructors using the textbook in their courses.Key Features:A unique teaching approach which merges mathematical methods and the Python programming skills which physicists and engineering students need in their coursesUses examples and models from physical and engineering systems, to motivate the mathematics being taughtStudents learn to solve scientific problems in three different ways: traditional pen-and-paper methods, using scientific numerical techniques with NumPy and SciPy, and using Symbolic Python (SymPy). This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 158,62
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierHardcover. Etat : Brand New. 520 pages. 10.00x7.00x10.00 inches. In Stock.
Edité par Taylor & Francis Ltd, London, 2024
ISBN 10 : 1032278366 ISBN 13 : 9781032278360
Langue: anglais
Vendeur : Grand Eagle Retail, Mason, OH, Etats-Unis
EUR 123,33
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : new. Hardcover. This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Both analytical and computational examples are integrated from its start. Each chapter concludes with a set of problems designed to help students hone their skills in mathematical techniques, computer programming, and numerical analysis. The book places less emphasis on mathematical proofs, and more emphasis on how to use computers for both symbolic and numerical calculations. It contains 182 extensively documented coding examples, based on topics that students will encounter in their advanced courses in Mechanics, Electronics, Optics, Electromagnetism, Quantum Mechanics etc.An introductory chapter gives students a crash course in Python programming and the most often used libraries (SymPy, NumPy, SciPy, Matplotlib). This is followed by chapters dedicated to differentiation, integration, vectors and multiple integration techniques. The next group of chapters covers complex numbers, matrices, vector analysis and vector spaces. Extensive chapters cover ordinary and partial differential equations, followed by chapters on nonlinear systems and on the analysis of experimental data using linear and nonlinear regression techniques, Fourier transforms, binomial and Gaussian distributions. The book is accompanied by a dedicated GitHub website, which contains all codes from the book in the form of ready to run Jupyter notebooks. A detailed solutions manual is also available for instructors using the textbook in their courses.Key Features:A unique teaching approach which merges mathematical methods and the Python programming skills which physicists and engineering students need in their coursesUses examples and models from physical and engineering systems, to motivate the mathematics being taughtStudents learn to solve scientific problems in three different ways: traditional pen-and-paper methods, using scientific numerical techniques with NumPy and SciPy, and using Symbolic Python (SymPy). This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
EUR 101,80
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierBuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Both analytical and computational examples are integrated from its start. Each chapter concludes with a set of problems designed to help students hone their skills in mathematical techniques, computer programming, and numerical analysis. The book places less emphasis on mathematical proofs, and more emphasis on how to use computers for both symbolic and numerical calculations. It contains 182 extensively documented coding examples, based on topics that students will encounter in their advanced courses in Mechanics, Electronics, Optics, Electromagnetism, Quantum Mechanics etc.An introductory chapter gives students a crash course in Python programming and the most often used libraries (SymPy, NumPy, SciPy, Matplotlib). This is followed by chapters dedicated to differentiation, integration, vectors and multiple integration techniques. The next group of chapters covers complex numbers, matrices, vector analysis and vector spaces. Extensive chapters cover ordinary and partial differential equations, followed by chapters on nonlinear systems and on the analysis of experimental data using linear and nonlinear regression techniques, Fourier transforms, binomial and Gaussian distributions. The book is accompanied by a dedicated GitHub website, which contains all codes from the book in the form of ready to run Jupyter not Elektronisches Buch. A detailed solutions manual is also available for instructors using the textbook in their courses.Key Features:A unique teaching approach which merges mathematical methods and the Python programming skills which physicists and engineering students need in their coursesUses examples and models from physical and engineering systems, to motivate the mathematics being taughtStudents learn to solve scientific problems in three different ways: traditional pen-and-paper methods, using scientific numerical techniques with NumPy and SciPy, and using Symbolic Python (SymPy). 488 pp. Englisch.
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
EUR 119,84
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierHRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
EUR 127,07
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierHRD. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 115,82
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : Brand New. 520 pages. 10.00x7.00x10.00 inches. In Stock. This item is printed on demand.
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 115,03
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierBuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Both analytical and computational examples are integrated from its start. Each chapter concludes with a set of problems designed to help students hone their skills in mathematical techniques, computer programming, and numerical analysis. The book places less emphasis on mathematical proofs, and more emphasis on how to use computers for both symbolic and numerical calculations. It contains 182 extensively documented coding examples, based on topics that students will encounter in their advanced courses in Mechanics, Electronics, Optics, Electromagnetism, Quantum Mechanics etc.An introductory chapter gives students a crash course in Python programming and the most often used libraries (SymPy, NumPy, SciPy, Matplotlib). This is followed by chapters dedicated to differentiation, integration, vectors and multiple integration techniques. The next group of chapters covers complex numbers, matrices, vector analysis and vector spaces. Extensive chapters cover ordinary and partial differential equations, followed by chapters on nonlinear systems and on the analysis of experimental data using linear and nonlinear regression techniques, Fourier transforms, binomial and Gaussian distributions. The book is accompanied by a dedicated GitHub website, which contains all codes from the book in the form of ready to run Jupyter not Elektronisches Buch. A detailed solutions manual is also available for instructors using the textbook in their courses.Key Features:A unique teaching approach which merges mathematical methods and the Python programming skills which physicists and engineering students need in their coursesUses examples and models from physical and engineering systems, to motivate the mathematics being taughtStudents learn to solve scientific problems in three different ways: traditional pen-and-paper methods, using scientific numerical techniques with NumPy and SciPy, and using Symbolic Python (SymPy).
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
EUR 122,19
Autre deviseQuantité disponible : 4 disponible(s)
Ajouter au panierEtat : New. PRINT ON DEMAND.
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
EUR 128,56
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierHardback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.