PySpark Certification Course Online

Module 1: Introduction to Spark & PySpark Setup

⏳ 1 week

• Topics: Spark architecture, cluster modes, installing PySpark

• Hands-on: Launch a local Spark session and run basic RDD operations

Module 2: RDDs and Core Transformations

⏳ 1 week

• Topics: RDD creation, map/filter, actions vs. transformations

• Hands-on: Build word-count and log-analysis pipelines using RDDs

Module 3: DataFrames & Spark SQL

⏳ 1 week

• Topics: DataFrame API, schema inference, SQL queries, temporary views

• Hands-on: Load JSON/CSV data into DataFrames and run SQL aggregations

Module 4: Data Processing & ETL

⏳ 1 week

• Topics: Joins, window functions, complex types, UDFs

• Hands-on: Cleanse and enrich a large dataset, applying window-based rankings

Module 5: Machine Learning with MLlib

⏳ 1 week

• Topics: Pipelines, feature engineering, classification, clustering

• Hands-on: Build and evaluate a logistic regression model on Spark

Module 6: Performance Tuning & Optimization

⏳ 1 week

• Topics: Partitioning, caching strategies, broadcast variables, shuffle avoidance

• Hands-on: Profile job stages and optimize a slow Spark job

Module 7: Deployment & Orchestration

⏳ 1 week

• Topics: Submitting jobs with spark-submit, YARN integration, Databricks notebooks

• Hands-on: Schedule and monitor a PySpark ETL workflow on a cluster

Module 8: Capstone Project

⏳ 1 week

• Topics: End-to-end big data pipeline design

• Hands-on: Implement a full-scale data pipeline: ingest raw logs, transform, analyze, and store results

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