
Explore STL algorithms, their common uses, and how to unlock their potential through intuition and lambdas. Develop algorithm intuition to complement your data structure knowledge and enhance your C++ programming skills.

Explore C++ compiler's perspective with Andreas Fertig, diving into implicit conversions, lambdas, and variadic templates using C++ Insights tool for deeper understanding of code mechanics.

Hands-on workshop on building distributed serverless Python applications using Google Cloud Platform services. Learn to connect multiple programs through databases, APIs, and event triggers for cloud-native development.

Learn to process data efficiently using Azure Functions and Python, exploring serverless computing, best practices, and practical use cases for scalable cloud applications.

Learn to deploy a Django project on serverless infrastructure using Google Cloud Platform. Covers manual deployment, database setup, media storage, secrets management, and automation techniques.

Explore PYNQ: Python-based platform integrating microprocessors, microcontrollers, and FPGAs. Learn to leverage programmable system-on-chips for embedded development using familiar Python ecosystem and Jupyter notebooks.

Explore how Apache Airflow bridges data science and infrastructure, enabling collaboration between teams and facilitating the development of flexible, observable, and resilient data pipelines.

Explore scaling Python with Dask on distributed systems, focusing on deployment challenges and solutions for cluster resource managers like Kubernetes, Yarn, and cloud platforms.

Explora el tracing distribuido con OpenTelemetry: conceptos, instrumentación automática y demostración práctica para monitorear sistemas distribuidos eficientemente.

Explore event-driven applications using Apache Kafka and Python. Learn about Kafka's capabilities, integration techniques, and real-time data streaming for modern application development.

Explore the transition from legacy code to open-source solutions, focusing on Python's advantages in software migrations and the implementation of robust frameworks like Apache Airflow.

Comprehensive exploration of Protocol Buffers, covering serialization, performance, encoding, and practical applications. Ideal for developers seeking to optimize data exchange in distributed systems.

Explore VigNET, an intelligent camera app using Vision Language Transformer to assist visually impaired users. Learn about its implementation, deployment, and open-source code for building your own visual question answering application.

Learn to scale data workflows using Apache Airflow, covering dynamic DAG generation, automation, and best practices for managing big data pipelines. Suitable for beginners and intermediate developers.

Explore using Open Policy Agent for SCM security management. Learn to implement governance and compliance controls in development processes using Python OPA Client for GitLab/GitHub.

Explore balancing privacy and utility in AI language models, focusing on protecting sensitive data while maximizing ChatGPT's benefits. Learn about PII removal, secure enclaves, and privacy-aware LLM applications.

Explore best practices for building serverless solutions with Python, focusing on API calls, streaming data, and ML inference. Learn techniques for production-grade systems with observability.

Streamline Python app deployment from local to cloud with CLI templates. Scaffold, provision, deploy, monitor, and set up CI/CD pipeline efficiently, saving time on infrastructure setup and configuration.

Explore Google Cloud's enhanced Python experience for building applications, pipelines, and analytics, focusing on BigQuery integration and DataFrame support for impactful business solutions.

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.

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.