What is 'Learning Scientific Programming with Python 2nd Edition' about?

'Learning Scientific Programming with Python 2nd Edition' is an educational resource that introduces readers to the principles of scientific programming using Python. This book covers essential programming concepts, data structures, and algorithms while emphasizing their application in scientific problems. It provides practical examples and exercises, making it suitable for students and professionals in scientific disciplines looking to harness Python's capabilities for data analysis and computational simulations.

Who is the intended audience for this book?

The book is primarily aimed at undergraduate and graduate students in scientific fields such as physics, chemistry, biology, and engineering. However, it can also benefit professionals and researchers in these domains who wish to enhance their programming skills and leverage Python for data analysis and modeling. By bridging theoretical concepts with practical examples, this book serves as a valuable resource for anyone eager to learn scientific programming.

What are the key topics covered in this edition?

This second edition covers a wide range of topics including Python basics, data types, control structures, functions, modules, and libraries crucial for scientific computation. It also delves into advanced topics like numerical methods, data visualization, and statistical analysis. Each chapter includes practical exercises and coding examples to facilitate hands-on learning, ensuring that readers can apply the concepts to real-world scientific challenges.

How does this book approach teaching Python for scientific purposes?

The book adopts a practical approach, using real-life scientific problems as examples to illustrate programming concepts. This hands-on methodology allows readers to understand how Python can be used to solve complex problems in various scientific fields. By integrating theory with practice, readers gain not only coding skills but also the confidence to implement solutions to their unique research challenges.

Are there any online resources or companion materials available?

Yes, many editions of learning textbooks, including 'Learning Scientific Programming with Python 2nd Edition', often accompany supplementary online resources such as coding exercises, video tutorials, and forums for discussion. These additional materials enhance the learning experience by allowing readers to practice coding in a guided environment and seek help on specific problems or concepts they may find challenging.

Can beginners in programming benefit from this book?

Absolutely! Although the book is designed with scientific applications in mind, it starts with foundational programming concepts. Beginners can build their skills progressively, starting from the basics of Python and gradually progressing to more complex topics related to scientific programming. The clear explanations and structured exercises make it accessible for readers without prior experience in coding.

What programming concepts does the book emphasize?

The book emphasizes a variety of programming concepts crucial for scientific programming, including data handling, looping, conditional statements, and function creation. Additionally, it highlights the use of libraries such as NumPy and Matplotlib, which are vital for numerical computing and data visualization, allowing readers to execute calculations and present data effectively within their scientific projects.

Is this book suitable for self-study?

Yes, 'Learning Scientific Programming with Python 2nd Edition' is well-structured for self-study. Each chapter progresses logically, with clear explanations, examples, and exercises that reinforce learning. This format allows readers to work at their own pace, making it an excellent choice for independent learners who want to enhance their programming skills in a scientific context.

Can this book help with data analysis in research projects?

Definitely! The skills and techniques taught in 'Learning Scientific Programming with Python 2nd Edition' are directly applicable to data analysis in research projects. By mastering Python and its libraries, readers can design algorithms to analyze data, visualize results, and derive insights, which are critical components of research across various scientific fields.

Where can I buy 'Learning Scientific Programming with Python 2nd Edition'?

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Learning Scientific Programming with Python

Master basic programming tasks with Python using real-life examples from science and engineering.

Item #: 41407950

Learning Scientific Programming with Python

87% of respondents would recommend this to a friend

Item #: 41407950

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What Stands Out

Comprehensive Curriculum

Covers fundamental programming concepts alongside advanced scientific techniques, making it suitable for beginners and experienced users alike. It fosters a deep understanding of Python's applications in scientific domains.

Practical Examples

Integrates real-world problems and hands-on exercises throughout the text, enhancing learner engagement and promoting immediate application of programming skills in scientific research.

Updated Content

Includes the latest Python libraries and tools, ensuring learners are equipped with current programming practices, which enhances their employability and ability to tackle contemporary scientific challenges.

Product Details

Learn basic programming tasks with real-life scientific examples in Python
Covers core Python 3 language, NumPy, SciPy, Matplotlib, and Jupyter Notebooks
Includes new chapter on data analysis with pandas library and updated content
Introduces advanced topics like floating-point precision and algorithm stability
Geared towards students and researchers needing a solid Python programming foundation
Comes with extensive online resources for further study

Publisher	Cambridge University Press
Publication date	December 10, 2020
Edition	2nd
Language	English
Print length	570 pages
ISBN-10	1108745911
ISBN-13	978-1108745918
Item Weight	2.34 pounds (1.06 kg)
Dimensions	6.69 x 1.29 x 9.61 inches (17 x 3.3 x 24.4 cm)

Who Should Buy?

Beginner Python Users
Ideal for those new to Python, offering clear explanations and practical examples to master programming skills.
Science Students
Great for students in scientific fields, providing programming tools and concepts applicable in data analysis and modeling.
Self-Learners
Perfect for independent learners who prefer structured, hands-on content that encourages exploration of scientific programming.

Advanced Programmers
Not suitable for experienced programmers seeking in-depth or complex topics beyond basic scientific programming methodologies.

Product Description

Learning Scientific Programming with Python

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Introductory & Beginning Editorial Review

Learning Scientific Programming with Python is an impressive book that provides a detailed description of Python language and thought-provoking questions that help in gaining practical knowledge. This extraordinary book has an eclectic array of problems that are intriguing programming exercises drawn from scientific literature. The author has done an excellent job by providing so many interesting challenges. The solutions to these problems are available on the author's online website. However, this book is strictly not for beginners or anyone without an above-average math background as a scientist or engineer. Critics have mentioned that the book is challenging to read, dense, and not suitable for learning. Still, others have praised it for building up a base understanding of Python and tailoring for more academic needs. Overall, it is five stars plus for the book.

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Pros

Detailed description of Python language.
Thought-provoking questions and problems.
Contains intriguing programming exercises drawn from scientific literature.
Solutions to problems are available online.
Helps build up the base understanding of Python.
Tailored for more academic needs
Reasonable price
Fast delivery

Cons

Not suitable for beginners

Product Price History

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Features & Benefits

Python is becoming more popular for scientific and engineering students and researchers.
Book covers basics to advanced concepts.
Includes libraries for numerical programming and data visualization.
New chapter on data analysis with pandas library.
Online resources available for further study.
Ideal for students seeking a foundation in Python programming.

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Learning Scientific Programming with Python

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