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

by ;
Edition: 1st
Format: Paperback
Pub. Date: 2019-02-15
Publisher(s): Pearson
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Summary

 

Author Biography

 

Table of Contents

Download PDF for a visual view of the Table of Contents.


PART 1

CS: Python Fundamentals Quickstart

CS 1. Introduction to Computers and Python

DS Intro: A Brief Tour of Data Science and Artificial Intelligence

CS 2. Introduction to Python Programming

DS Intro: Basic Descriptive Stats

CS 3. Control Statements; Program Development

DS Intro: Measures of Central Tendency—Mean, Median, Mode

CS 4. Functions

DS Intro: Basic Statistics— Measures of Dispersion

CS 5. Lists and Tuples

DS Intro: Simulation and Static Visualization

 

PART 2

CS: Python Data Structures, Strings and Files

CS 6. Dictionaries and Sets

DS Intro: Simulation and Dynamic Visualization

CS 7. Array-Oriented Programming: High-Performance NumPy Arrays

DS Intro: Pandas Series and DataFrames

CS 8. Strings: A Deeper Look; Regular Expressions

DS Intro: Pandas, Regular Expressions and Data Wrangling

CS 9. Files and Exceptions

DS Intro: Loading Datasets from CSV Files into Pandas DataFrames

 

PART 3

CS: Python High-End Topics

CS 10. Object-Oriented Programming

DS Intro: Time Series and Simple Linear Regression

CS 11. tkinter Graphical User Interfaces

CS 12. Computer Science Thinking: Recursion, Searching, Sorting and Big O

CS Other Topics Blog

 

PART 4

AI, Cloud and Big Data Case Studies

DS 13. Natural Language Processing (NLP), Web Scraping (in exercises)

DS 14. Data Mining Twitter®: Sentiment Analysis, JSON and Web Services

DS 15. IBM® Watson™ and Cognitive Computing

DS 16. Machine Learning: Classification, Regression and Clustering

DS 17. Deep Learning and Reinforcement Learning

DS 18. Big Data: Hadoop®, Spark™, NoSQL and IoT

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