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Explore high-performance distributed and async task queues using Celery in Python. Learn to create, manage, and visualize tasks for improved system performance and resource utilization.
Explore challenges and strategies for teaching AI in higher education, addressing its evolving nature, multidisciplinary aspects, and preparing students for future innovations and ethical considerations.
Explore Python-powered serverless observability techniques, including logging, metrics, and telemetry. Learn to instrument code and leverage cloud-native services for enhanced application monitoring and scalability.
Learn PyTorch for deep learning: train neural networks for image and text classification, explore tensor operations, automatic differentiation, and modern libraries like PyTorch Lightning for efficient GPU training.
Explore Meta's innovative approach to improving Python performance at scale by statically linking native extensions, featuring insights on linkers, loaders, and binary layout optimization.
Learn to create native cross-platform apps using Python and BeeWare. Build a single codebase that deploys to desktop and mobile, integrate third-party libraries, and access device hardware.
Explore Python's unique features and fundamental concepts, including mutability, object behavior, lambda functions, decorators, and iterables, to enhance your programming skills.
Explore zero-data model training using foundational models to create task-specific models without new data. Learn techniques for leveraging open-source tools in your projects.
Learn to monitor and reduce carbon emissions of Python code through observability techniques, custom metrics, and visualization tools. Gain practical skills for sustainable tech development.
Explore functional programming in Python, learning features and techniques to enhance program design. Discover alternative problem-solving approaches and expand your programming toolkit.
Unveiling Pydantic's latest innovation: a comprehensive demo and explanation of their newly announced platform, showcasing its features and potential impact on Python development.
Explore Ibis for high-speed data analysis across various backends. Learn dataframe operations, backend selection, and integration with Python data tools for efficient large-scale analytics.
Discover strategies for efficient Python project development and testing, focusing on minimizing resource usage and environmental impact while maximizing productivity.
Explore Python's internals by implementing C/C++-style pointers, covering syntax addition, custom builtins, object layout, lifecycle management, and garbage collection mechanisms.
Dive into API security for Python apps. Learn authentication, authorization, OWASP top 10 vulnerabilities, OAuth, OIDC, JWTs, and automated security testing. Practical examples using Flask and FastAPI.
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