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Test and sharpen your Python skills with seven guided projects that explore popular computer science challenges.
Computer science can feel unapproachable for those without a formal CS education. Fun Computer Science Projects in Python pulls back that curtain, illuminating several foundational CS concepts through creative, hands-on projects.
Each of the 7 projects is presented in a code-centric tutorial that gently introduces topics like interpreters, emulators, and machine learning without getting bogged down by complex theory. The projects showcase advanced Python language features and clean code principles while exploring interesting algorithms.
Chapters conclude with discussions of real-world applications of the topic and proposed exercises to extend the reader's skills. Covers Python 3.x Introduction
Part I: Interpreters
Chapter 1: The Smallest Possible Programming Language
Chapter 2: Writing a BASIC Interpreter
Part II: Computational Art
Chapter 3: Retro Image Processing
Chapter 4: A Stochastic Painting Algorithm
Part III: Emulators
Chapter 5: Building a CHIP-8 Virtual Machine
Chapter 6: Emulating the NES Game Console
Part IV: Super Simple Machine Learning
Chapter 7: Classification with K-Nearest Neighbors
Chapter 8: Regression with K-Nearest Neighbors
Afterword
Appendix: Bitwise Operations David Kopec is an associate professor of computer science at Champlain College. He is the author of five programming books, including the Classic Computer Science Problems series, and spent several years as an iOS developer for startups. In addition to his teaching work, David is an avid podcaster and indie app developer with an MS in Computer Science from Dartmouth and an EMBA from Quantic.
Computer science can feel unapproachable for those without a formal CS education. Fun Computer Science Projects in Python pulls back that curtain, illuminating several foundational CS concepts through creative, hands-on projects.
Each of the 7 projects is presented in a code-centric tutorial that gently introduces topics like interpreters, emulators, and machine learning without getting bogged down by complex theory. The projects showcase advanced Python language features and clean code principles while exploring interesting algorithms.
Chapters conclude with discussions of real-world applications of the topic and proposed exercises to extend the reader's skills. Covers Python 3.x Introduction
Part I: Interpreters
Chapter 1: The Smallest Possible Programming Language
Chapter 2: Writing a BASIC Interpreter
Part II: Computational Art
Chapter 3: Retro Image Processing
Chapter 4: A Stochastic Painting Algorithm
Part III: Emulators
Chapter 5: Building a CHIP-8 Virtual Machine
Chapter 6: Emulating the NES Game Console
Part IV: Super Simple Machine Learning
Chapter 7: Classification with K-Nearest Neighbors
Chapter 8: Regression with K-Nearest Neighbors
Afterword
Appendix: Bitwise Operations David Kopec is an associate professor of computer science at Champlain College. He is the author of five programming books, including the Classic Computer Science Problems series, and spent several years as an iOS developer for startups. In addition to his teaching work, David is an avid podcaster and indie app developer with an MS in Computer Science from Dartmouth and an EMBA from Quantic.