9780135404676-0135404673-Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud

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

ISBN-13: 9780135404676
ISBN-10: 0135404673
Edition: 1
Author: Paul Deitel, Harvey Deitel
Publication date: 2019
Publisher: Pearson
Format: Paperback 880 pages
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ISBN-13: 9780135404676
ISBN-10: 0135404673
Edition: 1
Author: Paul Deitel, Harvey Deitel
Publication date: 2019
Publisher: Pearson
Format: Paperback 880 pages

Summary

Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud (ISBN-13: 9780135404676 and ISBN-10: 0135404673), written by authors Paul Deitel, Harvey Deitel, was published by Pearson in 2019. With an overall rating of 4.1 stars, it's a notable title among other Cloud Computing (Networking & Cloud Computing, Prolog, Programming Languages) books. You can easily purchase or rent Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud (Paperback) from BooksRun, along with many other new and used Cloud Computing books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $45.55.

Description

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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