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Michael Conterio,
Martin O'Hanlon,
Andrew Collins,
Eirini K,
Laura Sach,
Mac Bowley,
and
Matt Hogan
Topics Covered
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Topics Covered
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Topics Covered
- Using widgets to build a GUI
- Responding to user inputs using events
- Reading and modifying the properties of widgets
- Designing GUIs and using boxes and either auto or grid layouts to implement them
- Adjusting the appearance of your GUI to improve the user experience
- Using time-based events
- Decomposing a project to make it more manageable
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Reading list
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If you are interested in learning about the best practices of user interface design, Wilbert O. Galitz's The Essential Guide to User Interface Design valuable resource. provides essential techniques on how to design compelling and effective user interfaces.
Chuck Easttom's User Interface Design and Evaluation introduces the fundamental principles of user interface design and evaluation while covering advanced concepts such as user research, design patterns, and mobile user interface design. It is beneficial for students, practitioners, and researchers in the field of human-computer interaction.
The Design of Everyday Things classic work by Donald A. Norman that explores the principles of user-centered design and how to create products that are both functional and enjoyable to use. While this book has a broader focus on design in general rather than specifically on GUIs, it offers valuable insights that can be applied to the design of graphical user interfaces.
Rapid GUI Programming with Python and Qt introduces the PyQt framework, which enables developers to create cross-platform GUI applications with Python. If you are interested in using Python for GUI development, this book great resource.
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JavaScript GUI Development with AngularJS explores the AngularJS framework, a popular JavaScript framework for building web applications. covers essential concepts of AngularJS and includes a chapter on building a GUI for a sample application, providing valuable insights for those interested in JavaScript GUI development.
Usability Engineering by Jakob Nielsen is an authoritative guide on usability engineering principles and best practices. provides foundational knowledge and principles, making it a valuable resource for improving the usability and user experience of GUIs and other user interfaces.
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Designing Interfaces is considered a classic work on the principles of user interface design. includes a wealth of practical advice, examples, and case studies, making it a valuable resource for those interested in improving the design and functionality of their user interfaces.
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Deep dive into Python's advanced features, covering metaprogramming, decorators, generators, and concurrency.
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Collection of practical recipes and solutions for common Python programming tasks, covering a wide range of topics.
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Is an introductory text to Python programming, with a focus on computational thinking and problem-solving.
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.
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Comprehensive guide to using Python for financial analysis and modeling, covering data manipulation, financial calculations, and visualization.
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Showcases a collection of real-world examples and case studies of successful widget implementations, providing practical insights and lessons learned.
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Comprehensive guide to the basics of Python programming, covering data types, control flow, functions, object-oriented programming, and debugging.
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Uses a creative and engaging approach to teach Python concepts, with a focus on visual learning and hands-on exercises.
Comprehensive guide to Python's data analysis ecosystem, including NumPy, Pandas, and Matplotlib, with a focus on practical applications.
Comprehensive guide to machine learning using Python, covering supervised and unsupervised learning, model evaluation, and deployment.
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Comprehensive guide to deep learning using Python, covering neural networks, convolutional neural networks, and recurrent neural networks.
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