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EDUCBA

The course follows a project-based approach, enabling learners to progressively apply, analyze, and demonstrate their understanding of GUI application development. Ideal for learners with basic Python skills, this course emphasizes event-driven programming concepts, widget manipulation, and practical data handling using native Python libraries.

By the end of the course, learners will be able to:

Construct CSV data files for use in GUI applications

Design interactive interfaces using PySide2 widgets

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The course follows a project-based approach, enabling learners to progressively apply, analyze, and demonstrate their understanding of GUI application development. Ideal for learners with basic Python skills, this course emphasizes event-driven programming concepts, widget manipulation, and practical data handling using native Python libraries.

By the end of the course, learners will be able to:

Construct CSV data files for use in GUI applications

Design interactive interfaces using PySide2 widgets

Implement data integration and display logic in a real-world desktop app

Demonstrate output in a working GUI environment

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Syllabus

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Activities

Coming soon We're preparing activities for PySide2 Project - Data Fetching Application. These are activities you can do either before, during, or after a course.

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Learners who complete PySide2 Project - Data Fetching Application will develop knowledge and skills that may be useful to these careers:

Reading list

We haven't picked any books for this reading list yet.
This pragmatic guide offers a concise overview of Python's core language features. It's a useful resource for developers who want to quickly grasp the essentials and key concepts of Python without a lengthy introduction.
Great introduction to computer science for beginners. It covers a variety of topics, from algorithms and data structures to object-oriented programming and functional programming.
Is an excellent starting point for beginners who want to learn the basics of Python programming. It covers a wide range of topics, from the fundamentals of the language to more advanced concepts like object-oriented programming and data structures.
Ideal for beginners who want to quickly apply Python to practical tasks. focuses on using Python to automate everyday computer tasks, such as working with files, web scraping, and sending emails. It assumes no prior programming experience and is highly regarded for its clear, step-by-step instructions and focus on immediate productivity gains. The second edition widely used and practical resource.
Uses Python to introduce fundamental computer science concepts. It's a good choice for students or self-learners who want to learn programming within the context of computer science principles. The 3rd edition provides a solid foundation in both Python and computational thinking.
Must-read for anyone who wants to improve their Python programming skills. It covers a variety of advanced topics, from metaprogramming and decorators to generators and coroutines.
Comprehensive reference guide that covers all aspects of the Python language. It great resource for experienced programmers who need to quickly look up information.
Great introduction to data analysis with Python. It covers a variety of topics, from data cleaning and wrangling to data visualization and machine learning.
Great introduction to data analysis for finance with Python. It covers a variety of topics, from data cleaning and wrangling to data visualization and machine learning.
Comprehensive introduction to Python programming. It covers a wide range of topics, from the fundamentals of the language to more advanced concepts like object-oriented programming and data structures.
Is an excellent starting point for anyone new to Python or programming in general. It covers fundamental programming concepts and Python basics with a hands-on, project-based approach, making it very practical for beginners. The third edition is updated to cover newer Python versions and is widely recommended for its clear explanations and engaging projects. It's often used as an introductory textbook.
Is highly recommended for intermediate to advanced Python programmers looking to write more idiomatic and efficient code. It explores Python's often-overlooked features and best practices, delving into topics like data structures, the Python data model, and metaprogramming. It's a valuable resource for deepening understanding and is considered a must-read for those aiming for mastery.
A collection of practical tips and techniques for writing better Python code. focuses on Pythonic practices, lesser-known functionality, and built-in tools to help developers write cleaner, faster, and more robust code. It's suitable for those with a basic understanding of Python who want to improve their coding style and efficiency.
Essential for anyone interested in using Python for data science and analysis. Written by the creator of the pandas library, this book provides comprehensive guidance on manipulating, processing, cleaning, and crunching datasets using pandas, NumPy, and Jupyter. The 3rd edition is updated for recent library versions and standard reference in the data science community.
Offers a collection of tips and tricks to help intermediate Python developers write more professional and Pythonic code. It provides concise explanations and practical examples of various Python features, making it a useful resource for leveling up coding skills and discovering best practices.
While not exclusively a Python book, 'Clean Code' foundational text for any programmer. It teaches principles of writing readable, maintainable, and well-structured code, which are crucial for developing robust applications in Python. provides valuable context and best practices that complement Python-specific knowledge.
A classic computer science textbook that covers fundamental algorithms and data structures. While not Python-specific, understanding these concepts is essential for writing efficient Python programs, especially in technical or academic settings. provides the theoretical foundation necessary for tackling complex problems with Python.
Following up on 'Automate the Boring Stuff,' this book delves into writing cleaner and more maintainable Python code. It covers topics like code formatting, refactoring, and testing, which are essential for building larger and more complex projects.

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