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Lauren Hyams, Marc Scott, Rik Cross, Laura Sach, Janina A, Caitlyn Merry, Martin O'Hanlon, Laura Koponen, Siim Põder, Michael Conterio, Mac Bowley, and Diane Dowling

Topics Covered

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Topics Covered

  • Introduce the principles of object-oriented programming in Python.
  • Understand the difference between a function and an object.
  • Create objects, functions, methods, and classes.
  • Write a text-based adventure game.
  • Extending other people’s classes, including inheritance and polymorphism.
  • Share your code with other learners, and see theirs.
  • Develop ideas for using object-oriented programming in the classroom.

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Reading list

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Comprehensive guide to the basics of Python programming, covering data types, control flow, functions, object-oriented programming, and debugging.
Comprehensive guide to Python's data analysis ecosystem, including NumPy, Pandas, and Matplotlib, with a focus on practical applications.
Comprehensive guide to deep learning using Python, covering neural networks, convolutional neural networks, and recurrent neural networks.
Concise and comprehensive reference to the Python language, covering syntax, built-in functions and objects, and advanced topics.
Comprehensive guide to the Python Standard Library, covering its vast collection of modules and their applications.
Practical guide to testing Python code using the pytest framework, covering unit testing, integration testing, and end-to-end testing.
Practical guide to using Python for bioinformatics tasks, covering sequence analysis, genome assembly, and data visualization.
Comprehensive guide to using Python for financial analysis and modeling, covering data manipulation, financial calculations, and visualization.
Introduces object-oriented programming (OOP) using C++, covering basic concepts, data structures, and algorithms. It emphasizes code simplicity and clarity, making it suitable for beginners or those new to OOP.
Is an introduction to programming and computer science using Python, focusing on OOP concepts. It covers fundamental data structures, algorithms, and design patterns, providing a solid understanding of OOP principles.
Provides a practical guide to object-oriented analysis and design (OOAD), exploring concepts and techniques for developing well-structured and maintainable software. It emphasizes real-world examples and case studies, making it accessible to both beginners and experienced developers.
Introduces OOP concepts and Java programming, providing a comprehensive overview of OOP principles. It covers encapsulation, inheritance, polymorphism, and design patterns, making it suitable for beginners or those new to OOP.
This classic book introduces design patterns, which are reusable solutions to common software design problems. It explores 23 patterns, providing insights into their implementation and usage, making it essential for experienced developers seeking to improve their OOP skills.
Practical guide to using Python for basic automation tasks, providing a gentle introduction to Python's core concepts and its practical applications.

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