📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of Apache Spark Basics, from foundations to a certified capstone project.
Outline
Understand Spark ecosystem and advantages over traditional frameworks • Explore core components and architecture • Set up Spark environment for hands‑on labs
Outline
Manipulate data using RDDs and DataFrames • Write efficient transformations and actions • Optimize performance with caching and partitioning
Outline
Apply MLlib algorithms to build machine‑learning models • Integrate Spark with TensorFlow and PyTorch • Deploy scalable AI pipelines on Spark clusters
Outline
Implement real‑time stream processing with Structured Streaming • Handle massive datasets using Spark SQL and Catalyst optimizer • Tune jobs for high‑throughput AI workloads
Outline
Explore Spark use‑cases in healthcare, finance, and e‑commerce • Analyze performance tuning techniques • Adopt best practices for production AI systems
Outline
Design an end‑to‑end Spark AI solution • Implement data ingestion, model training, and deployment • Present findings and receive expert feedback
Earn government-registered certification in Apache Spark Basics
e-Certificate and e-Marksheet issued on successful completion.
