Data Engineering
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Gain in-depth skills to administer and scale Apache Airflow—from configuring executors and users to building DAGs, integrating with AWS/Azure, and creating custom plugins.
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Master Apache Airflow workflows using Python—from setting up executors and building DAGs to deploying production pipelines, cloud integration, and custom plugins.
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Data Engineering Automation: Ansible, Apache Airflow, and Snowflake (5 days, online)
Master data engineering automation—from provisioning infrastructure with Ansible to orchestrating workflows with Apache Airflow and integrating with Snowflake for modern cloud data warehousing.
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Distributed Task Automation with Python Celery and RabbitMQ (16 hours, online)
Gain hands‑on mastery of distributed task automation using Python, Celery & RabbitMQ. Set up Docker environments, define tasks, and scale workflows with routing, scheduling, and deployment.
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Jupyter Widgets Programming (3 days, online)
The Jupyter Widgets Programming course instructs Python and JavaScript/TypeScript developers on extending Jupyter Labs/Notebooks with customized widgets, covering both high-level and low-level concepts and offering the option to use either JavaScript or TypeScript.
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Distributed Task Automation with Python Faust and Kafka (16 hours, online)
Master distributed task automation with Python Faust and Kafka. Learn to containerize environments, process streaming data, manage state and fault tolerance, monitor systems, and deploy real‑time pipelines.
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Generative AI and LLMs for Python Programmers (5 days, online)
This course offers an in-depth exploration of Generative AI and Large Language Models, covering their evolution, architecture, practical applications, project lifecycle, advanced techniques, and ethical considerations.
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Practical Apache Spark for Data Pipelines (21 hours, online)
Learn to build scalable data pipelines with Apache Spark using Python. Gain hands-on experience with Spark Core, SQL, DataFrames, and real-time processing.
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Task Automation with Python (14 hours, online)
Streamline workflows with Python by automating file ops, subprocesses, logging, CLI args, async and API tasks—plus optional AI and distributed automation modules.