Intro to Python for Computer Science and Data Science : Learning to Program with AI, Big Data and the Cloud /

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For introductory-level Python programming and/or data-science courses. A groundbreaking, flexible approach to computer science and data science...

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Detalles Bibliográficos
Autores principales: Deitel, Paul (Autor), Deitel, Harvey (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Pearson, 2019.
Edición:1st edition.
Temas:
Python (Computer program language)
Python (Langage de programmation)
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 |a This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For introductory-level Python programming and/or data-science courses. A groundbreaking, flexible approach to computer science and data science The Deitels' Introduction to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud offers a unique approach to teaching introductory Python programming, appropriate for both computer-science and data-science audiences. Providing the most current coverage of topics and applications, the book is paired with extensive traditional supplements as well as Jupyter Notebooks supplements. Real-world datasets and artificial-intelligence technologies allow students to work on projects making a difference in business, industry, government and academia. Hundreds of examples, exercises, projects (EEPs), and implementation case studies give students an engaging, challenging and entertaining introduction to Python programming and hands-on data science. The book's modular architecture enables instructors to conveniently adapt the text to a wide range of computer-science and data-science courses offered to audiences drawn from many majors. Computer-science instructors can integrate as much or as little data-science and artificial-intelligence topics as they'd like, and data-science instructors can integrate as much or as little Python as they'd like. The book aligns with the latest ACM/IEEE CS-and-related computing curriculum initiatives and with the Data Science Undergraduate Curriculum Proposal sponsored by the National Science Foundation. 
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