Big Data Analytics with Apache Spark 3
Enable participants to build scalable analytics solutions with Spark MLlib and Structured Streaming.
Get Course Info
Audience: Data Scientists / Data Engineers
Duration: 4 days
Format: Lectures and hands‑on labs
Overview
This course focuses on advanced analytics techniques using Apache Spark 3, including machine learning with MLlib and real‑time streaming analytics.
Objective
Enable participants to build scalable analytics solutions with Spark MLlib and Structured Streaming.
What You Will Learn
- MLlib pipelines and algorithms
- Structured Streaming for real‑time data
- Graph analytics with GraphFrames (optional)
Course Details
Audience: Data Scientists / Data Engineers
Duration: 4 days
Format: Lectures and hands‑on labs
Prerequisites:
Spark Essentials or equivalent experience
Setup: Databricks or on‑prem Spark cluster
Detailed Outline
- ML pipelines
- Feature engineering
- Classification and regression algorithms
- Streaming sources and sinks
- Windowed aggregations
- Exactly‑once guarantees
- Building a real‑time dashboard with streaming data
- Training and evaluating ML models at scale
Ready to Get Started?
Contact us to learn more about this course and schedule your training.