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.
Applied Learning Project
Learners will complete hands-on projects that simulate real-world challenges such as designing ETL pipelines, building predictive ML models, segmenting customers with clustering, and processing unstructured text data. These projects ensure participants can confidently apply Spark and Python to solve authentic big data problems across industries.
