Learn to build robust ML pipelines with RAG technology, model evaluation metrics, and SHAP explainability. Essential guide for AI/data engineers.

Master data pipeline orchestration for ETL, ML & AI. Compare top tools, learn best practices, and level up your data engineering skills.

Discover the best data ingestion tools and platforms in the modern age. Master data ingestion using Python with practical code examples and tutorials.

Master Retrieval Augmented Generation (RAG) pipelines for AI systems. Explore architectures, tools, implementation, and best practices for RAG in data engineering.

Mage Pro is a fully managed, scalable data pipeline platform that builds on the open-source Mage by adding enterprise security, team collaboration, 24/7 support, and automated infrastructure management. It offers a simpler, faster, and more cost-effective alternative to Airflow, Dagster, Prefect, and dbt Cloud, making it ideal for teams ready to scale or upgrade from Mage OSS.

This guide demonstrates how to integrate your Mage Pro environment with Visual Studio Code and Cursor. By implementing Tailscale VPN and Remote SSH connections, you'll gain the ability to develop and manage your data pipelines directly within your preferred code editor, enhancing your development workflow and productivity. The integration provides a coding experience with full access to your Mage Pro features while leveraging the advanced editing capabilities of modern code editors.

Learn to build scalable data transformation pipelines in Python. Compare ETL/ELT tools, explore best practices, and implement production-ready solutions.

Learn data engineering fundamentals in Python - build ETL pipelines, master tools like Airflow and Spark, and leverage cloud platforms for scalable data workflows.