Spark and Python for Big Data with PySpark
About this course
This specialization provides a complete learning pathway in Apache Spark and Python (PySpark) for big data analytics, machine learning, and scalable data processing. Learners will begin with foundational Python and PySpark techniques, advance to predictive modeling and clustering, and explore advanced data workflows including ETL pipelines, streaming, and real-time processing. By the end, participants will be equipped with practical skills to design, build, and optimize distributed applications for data engineering, analytics, and business intelligence.
67/100
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- 31/45
- Who stands behind it
- 20/35
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- 16/20
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What you'll learn
- understand foundational Python and PySpark techniques
- apply predictive modeling and clustering
- design ETL pipelines
- manage real-time data processing
Course objectives
- equip learners with skills to build distributed applications
- prepare participants for roles in data engineering and analytics
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