Apache Spark 3 for Data Engineering & Analytics with Python

Learn how to use Python and PySpark 3.0.1 for Data Engineering / Analytics (Databricks) - Beginner to Ninja

Created by: David Charles Academy
Senior Big Data Engineer / Consultant at ABN AMRO

What Will I Learn?

• Learn the Spark Architecture
• Learn Spark Execution Concepts
• Learn Spark Transformations and Actions using the Structured API
• Learn Spark Transformations and Actions using the RDD (Resilient Distributed Datasets) API
• Learn how to set up your own local PySpark Environment
• Learn how to interpret the Spark Web UI
• Learn how to interpret DAG (Directed Acyclic Graph) for Spark Execution
• Learn the RDD (Resilient Distributed Datasets) API (Crash Course)
• Learn the Spark DataFrame API  (Structured APIs)
• Learn Spark SQL
• Learn Spark on Databricks
• Learn to Visualize (Graphs and Dashboards) Data on Databricks

Requirements

• A basic laptop PC running Windows or Mac OS with at least 6 - 8GB of RAM
• Basic programming knowledge

Target audience

• Python Developers who wish to learn how to use the language for Data Engineering and Analytics with PySpark
• Aspiring Data Engineering and Analytics Professionals
• Data Scientists / Analysts who wish to learn an analytical processing strategy that can be deployed over a big data cluster
• Data Managers who want to gain a deeper understanding of managing data over a cluster