- Introduction to Apache Spark: Overview of Spark architecture and its components (Spark Core, SQL, Streaming, MLlib, GraphX).
- Data Processing with Spark:Working with RDDs, DataFrames, and Datasets for large-scale data processing.
- Spark SQL and DataFrames:Querying structured data using Spark SQL and DataFrames.
- Real-Time Data Processing:Implementing structured streaming for real-time analytics.
- Optimization Techniques:Performance tuning, managing partitions, and caching strategies in Spark.
- Hands-on Projects: Practical applications in ETL, data analysis, and machine learning with Spark.
