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Hands-on introduction to Python basics for absolute beginners. Learn about data types, conditionals, loops, and user input through interactive exercises and practical programming examples.
Explore Python comprehensions: learn to write and utilize list, set, and dict comprehensions, nested comprehensions, and generator expressions. Understand their advantages over regular loops.
Hands-on tutorial for Python users to master SQLite, covering advanced SQL features, data manipulation with sqlite-utils, and exploration using Datasette. Learn to build and deploy data applications.
Learn to create a robust GraphQL API with Python and Strawberry, focusing on authentication, performance, and type safety. Explore real-time APIs and frontend integration using Django.
Learn to build modern web apps using Python, HTMX, and Tailwind CSS. Simplify development with hypermedia-driven architecture and streamlined design processes.
Learn techniques for analyzing and visualizing massive datasets using Python libraries like Dask and hvPlot. Explore efficient data formats, parallel computation, cloud resources, and interactive visualization for large-scale data science projects.
Explore feature engineering techniques for data visualization, automation, and machine learning. Learn to create and select features from various data types using encodings, vectorization, and date manipulation.
Learn to create interactive GUIs and web apps using streamlit in Python. Hands-on exercises cover basics, data visualization, custom layouts, and integration with popular libraries for effective data science projects.
Learn to create serverless Python web apps using PyScript. Explore project setup, data handling, DOM manipulation, JavaScript integration, and optimization techniques for browser-based Python development.
Aprenda a criar um pacote Python usando programação literária, combinando explicações em linguagem natural com código. Explore ferramentas como Jupyter Notebooks e Nbdev para desenvolvimento eficiente e documentação integrada.
Comprehensive guide to object-oriented programming in Python, covering design, inheritance, special methods, and converting procedural code to OOP through practical examples.
Learn to enhance Python functions using decorators. Explore their inner workings, create custom decorators, and discover how they simplify code and improve readability in popular libraries and frameworks.
Discover how to optimize Python code performance using Numba, a JIT compiler for numerical calculations. Learn when and how to apply Numba effectively to speed up math-heavy code in data science and development projects.
Learn to create, generate, host, and automate up-to-date API documentation using Sphinx and GitHub Actions, integrating it seamlessly into your software development lifecycle.
Learn to apply Python skills to pressing environmental issues, using tools like numpy, pandas, and matplotlib to analyze deforestation, wildlife trade, and carbon pollution data.
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