Computational and Inferential Thinking: The Foundations of Data Science
by Ani Adhikari, John DeNero
Publisher: GitBook 2017
Number of pages: 646
Data Science is about drawing useful conclusions from large and diverse data sets through exploration, prediction, and inference. Our primary tools for exploration are visualizations and descriptive statistics, for prediction are machine learning and optimization, and for inference are statistical tests and models.
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by Bradley Kjell - Central Connecticut State University
The text for a first course in computer science using the programming language Java. It covers the fundamentals of programming and of computer science. It is assumed that you have the Java version 5.0 or later and a text editor such as Notepad.
An electronic book for teaching Computational Science and Engineering. The intended audience are students in science and engineering at the advanced undergraduate level and higher. Tutorials for networking and visualization software are included.
by Christos Kalloniatis - InTech
This book may assist researchers on studying the innovative functions of modern information systems in various areas like health, telematics, knowledge management, etc. It can also assist young students in capturing the new research tendencies.
by Michal Armoni, Moti Ben-Ari - Weizmann Institute of Science
This book will familiarize you with the Scratch visual programming environment, focusing on using Scratch to learn computer science. Each concept is introduced in order to solve a specific task such as animating dancing images or building a game.