Applied Python Data Engineering Specialization
Master Python data engineering. Learn Hadoop, Spark, Snowflake, and data workflows for scalable solutions.
Master Python data engineering. Learn Hadoop, Spark, Snowflake, and data workflows for scalable solutions.
This comprehensive specialization teaches advanced data engineering skills using Python. Students learn to build and scale data pipelines using Hadoop, Spark, Snowflake, and Databricks, implement machine learning workflows with PySpark and MLFlow, and create impactful data visualizations. The program covers essential concepts in big data, distributed computing, containerization, and DataOps practices, preparing professionals for real-world data engineering challenges.
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What you'll learn
Create and optimize scalable data pipelines using Hadoop, Spark, and Snowflake, implement machine learning workflows with PySpark and MLFlow on Databricks, master containerization and orchestration with Docker and Kubernetes, develop impactful data visualizations and storytelling techniques, apply DataOps practices for continuous integration and deployment.
Skills you'll gain
This course includes:
65 Hours PreRecorded video
8 quizzes and assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 courses in this program
Spark, Hadoop, and Snowflake for Data Engineering
Course 1 · 29 Hours to complete · 4 modules
Virtualization, Docker, and Kubernetes for Data Engineering
Course 2 · 27 Hours to complete · 4 modules
Data Visualization with Python
Course 3 · 9 Hours to complete · 4 modules
Fee Structure
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