Apache Spark 3 for Data Engineering and Analytics with Python
Learn how to use Python and PySpark 3.0.1 for Data Engineering/Analytics (Databricks) - Beginner to Ninja
Created by David Mngadi
Explore how to harness the power of Apache Spark 3 and Python for data engineering and analytics. Gain practical experience with PySpark, working through real-world data tasks and building your skills in managing and analyzing large datasets.
Packt | Aug 2021 | 510 min
What You Will Learn
You will work through hands-on exercises that guide you from setting up your Spark environment to building and running data pipelines. Interactive activities and practical challenges help reinforce each concept, ensuring you gain confidence with PySpark and Databricks tools as you progress.
Key Features
- Analyze and process big data efficiently using PySpark DataFrames and SQL
- Set up and navigate Spark environments including Databricks for hands-on analytics
- Visualize and interpret data using Spark's structured APIs and dashboards
Target Audience
Ideal for Python developers and data professionals aiming to expand into big data analytics. If you have some experience with Python and want to learn scalable data engineering techniques using PySpark, this course will help you build practical skills for real-world projects.
