Intro to Python for Computer Science and Data Science

Intro to Python for Computer Science and Data Science
PDF, ePUB
  • eBook:
    Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud
  • Author:
    Paul J. Deitel, Harvey Deitel
  • Edition:
    1 edition
  • Categories:
  • Data:
    February 25, 2019
  • ISBN:
    0135404673
  • ISBN-13:
    9780135404676
  • Language:
    English
  • Pages:
    880 pages
  • Format:
    PDF, ePUB

Book 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.

Content

1. Introduction to Computers and Python
2. Introduction to Python Programming
3. Control Statements and Program Development
4. Functions
5. Sequences: Lists and Tuples
6. Dictionaries and Sets
7. Array-Oriented Programming with NumPy
8. Strings: A Deeper Look
9. Files and Exceptions
10. Object-Oriented Programming
11. Computer Science Thinking: Recursion, Searching, Sorting and Big O
12. Natural Language Processing (NLP)
13. Data Mining Twitter
14. IBM Watson and Cognitive Computing
15. Machine Learning: Classification, Regression and Clustering
16. Deep Learning
17. Big dаta: Hadoop, Spark, NoSQL and IoT

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