Computational and Inferential Thinking: The Foundations of Data Science
by Ani Adhikari, John DeNero
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 Hans-Peter Bischof
This text is an introduction to the formal study of computation. The course will provide students with a broad perspective of computer science and will acquaint them with various formal systems on which modern computer science is based.
by Susan Rodger - Duke University
These lecture notes present an introduction to theoretical computer science including studies of abstract machines, the language hierarchy from regular languages to recursively enumerable languages, noncomputability and complexity theory.
by Christine Alvarado, et al. - Harvey Mudd College
Our objective is to provide an introduction to computer science as an intellectually vibrant field rather than focusing exclusively on computer programming. We emphasize concepts and problem-solving over syntax and programming language features.
by Tony Hey, Stewart Tansley, Kristin Tolle - Microsoft Research
The Fourth Paradigm, the collection of essays expands on the vision of pioneering computer scientist Jim Gray for a new, fourth paradigm of discovery based on data-intensive science and offers insights into how it can be fully realized.