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    • Think Python: How to Think Like a Computer Scientist - 2e
    Tác giả : B. Downey, Allen;  Người hướng dẫn: -;  Đồng tác giả: - (2012)

    "Think Python is a concise introduction to software design using the Python programming language. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. This textbook has been used in classes at Bard College, Olin College of Engineering, University of California, Santa Barbara, University of Maine, University of Northern Colorado."
    • How to Think Like a Computer Scientist: Learning with Python
    Tác giả : Downey, Allen; Elkner, Jeff; Meyers, Chris;  Người hướng dẫn: -;  Đồng tác giả: - (2008)

    Allen Downey is an American computer scientist, Professor of Computer Science at the Franklin W. Olin College of Engineering and writer of free textbooks. Downey received in 1989 his BS and in 1990 his MA, both in Civil Engineering from the Massachusetts Institute of Technology, and his PhD in Computer Science from the University of California at Berkeley in 1997. He started his career as Research Fellow in the San Diego Supercomputer Center in 1995. In 1997 he became Assistant Professor of Computer Science at Colby College, and in 2000 at Wellesley College. He was Research Fellow at Boston University in 2002 and Professor of Computer Science at the Franklin W. Olin College of Engineering since 2003. In 2009-2010 he was also Visiting Scientist at Google Inc. Jeffrey Elkner is a h...
    • Introduction to Scientific Programming with Python
    Tác giả : Sundnes, Joakim;  Người hướng dẫn: -;  Đồng tác giả: - (2020)

    This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fun...