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Think Complexity: Exploring Complexity Science with Python
Allen B. Downey · Olin College
Có trong mục lục: 1.04: Complexity engineering
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Structure and Interpretation of Computer Programs
Harold Abelson, Gerald Sussman & Julie Sussman · Massachusetts Institute of Technology
The material in this book has been the basis of MIT's entry-level computer science subject and emphasizes several new themes. The most important of these is the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming, lazy evaluation, and nondeterministic programming. We have included new sections on concurrency and nondeterminism, and we have tried to integrate this theme throughout the book.
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Data Structures
Wikipedia · LibreTexts
This book is about the creation and analysis of efficient data structures. To understand the material in this book you should be comfortable enough in a programming language to be capable of working with and writing your own variables, arithmetic expressions, if-else conditions, loops, subroutines (also known as functions), pointers (also known as references or object handles), structures (also known as records or classes), simple input and output, and simple recursion.
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Principles of Data Science
OpenStax · LibreTexts
Principles of Data Science is intended to support one- or two-semester courses in data science. It is appropriate for data science majors and minors as well as students concentrating in business, finance, health care, engineering, the sciences, and a number of other fields where data science has become critically important.
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CSCI 110: Programming with C++
Sandra Ruiz · Crafton Hills College
Introduction to computer science, including programming, theory, and applications. Introduction to computer software design, implementation, methods, environment, and problem solving using the C++ language. Topics include data types, variables, expressions, input/output, control structures, functions, arrays, strings, and introduction to object-oriented programming
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The Crystal Ball - Instruction Manual I: Introduction to Data Science
Stephen Davies · University of Mary Washington
A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks.
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CISP 430: Data Structures
Suha Aljuboori · Folsom Lake College
This course applies object-oriented techniques for systematic problem analysis and the managing of program complexity using abstraction. Specifications, design, coding, testing, and documentation of large multi-file programs are covered. It uses advanced language features such as classes, strings, non-text files, pointers, and recursion. Abstract data types such as stacks, queues, lists, binary trees, heaps/priority queues, hash tables, and graphs are examined.
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Foundations of Computation
Carol Critchlow & David J. Eck · Hobart and William Smith Colleges
Foundations of Computation is a free textbook for a one-semester course in theoretical computer science. The course has no prerequisites other than introductory computer programming. The first half of the course covers material on logic, sets, and functions that would often be taught in a course in discrete mathematics. The second part covers material on automata, formal languages, and grammar that would ordinarily be encountered in an upper level course in theoretical computer science.
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A Guide to MATLAB
Austin Bray & Reza Montazami · LibreTexts
This textbook provides an introduction to the MATLAB programming language for first-year mechanical engineering students enrolled in ME 160. Designed to follow the content taught in class, this book provides a supplement to in-class learning that is presented at a level that is understandable to a student with no experience coding before coming to Iowa State University.
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Think Data Structures - Algorithms and Information Retrieval in Java
Allen B. Downey · Olin College
This book is intended for college students in computer science and related fields, as well as professional software engineers, people training in software engineering, and people preparing for technical interviews.
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Math, Numerics, and Programming (for Mechanical Engineers)
Masayuki Yano, James Douglass Penn, George Konidaris, & Anthony T Patera · Massachusetts Institute of Technology
This text introduces elementary programming concepts including variable types, data structures, and flow control. After an introduction to linear algebra and probability, it covers numerical methods relevant to mechanical engineering, including approximation (interpolation, least squares and statistical regression), integration, solution of linear and nonlinear equations, ordinary differential equations, and deterministic and probabilistic approaches.
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The Data Renaissance
J.J. Sylvia IV · Fitchburg State University
The Data Renaissance delves into the complexities of data's role in various industries and its broader impact on society. It highlights the challenges in investigating data practices, citing examples like TikTok, where algorithms and data handling are closely guarded secrets. The content, contributed by students under the guidance of an expert, covers a wide range of topics, including the ethical aspects of generative AI in education and the workplace.
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Delftse Foundations of Computation
Stefan Hugtenburg & Neil Yorke-Smith · Delft University of Technology
Delftse Foundations of Computation is a textbook for a one quarter introductory course in theoretical computer science. It includes topics from propositional and predicate logic, proof techniques, set theory and the theory of computation, along with practical applications to computer science. It has no prerequisites other than a general familiarity with computer programming.
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Computer Science from the Bottom Up
Ian Wienand · Red Hat
Computer science is often taught from the "top down"; applications, high level programming, software design and development theory, possibly data structures. Students will probably be exposed to binary, hopefully binary logic, possibly even some low level concepts such as registers, opcodes and the like at a superficial level. This book aims to move in completely the opposite direction, working from operating systems fundamentals through to how those applications are complied and executed.
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Pharo by Example 5.0
Ducasse, Zagidulin, Hess, and Chloupis · LibreTexts
Pharo by Example 5.0, intended for both students and developers, will guide you gently through the Pharo language and environment by means of a series of examples and exercises. In Pharo everything is an object, and anything can change at run-time under your fingers. Pharo is written in itself so you can explore a complete world. You can feel and talk to objects.
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Discrete Mathematics for Computer Science
Mark A. Fitch · University of Alaska Anchorage
In class materials for an introduction to logic, proof, enumeration, relations, and graph theory for lower division undergraduate students of computer science and computer systems engineering. These materials were designed to introduce concepts of logic and discrete mathematics via carefully picked problems that test understanding of definitions. Another source of exercises is required at this time.
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Byte of Python
Swaroop C H · LibreTexts
"A Byte of Python" is a free book on programming using the Python language. It serves as a tutorial or guide to the Python language for a beginner audience. If all you know about computers is how to save text files, then this is the book for you.
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Laboratory Manual - Computer Programming with Python, Multisim and TINA/4E
James M. Fiore · Mohawk Valley Community College
This laboratory manual is intended for use in an introductory computer programming course for electrical engineering technology students. It begins with a basic explanation of schematic capture and simulation tools and proceeds to the Python programming language.
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Think Java - How to Think Like a Computer Scientist
Allen B. Downey · lin College
Think Java is an introduction to computer science and programming intended for readers with little or no experience. We start with the most basic concepts and are careful to define all terms when they are first used. The book presents each new idea in a logical progression. Larger topics, like recursion and object-oriented programming, are divided into smaller examples and introduced over the course of several chapters.
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Algorithm Design and Analysis
Godfry Justo · African Virtual University
There are both practical and theoretical reasons to study algorithms. From a practical standpoint, you have to know a standard set of important algorithms from different areas of computing; in addition, you should be able to design new algorithms and analyze their efficiency. From the theoretical standpoint, the study of algorithms, sometimes called algorithmics, has come to be as the cornerstone of computer science.