---
title: "Data Engineering with Spark"
description: "Master data engineering with Apache Spark through Vidya's hands-on training course. Learn to build scalable, fault-tolerant data pipelines, process big data, and leverage Spark's powerful features for real-world data engineering challenges."
canonical: https://www.vidyasource.com/courses/data-engineering-with-spark/
type: course
tags: ["Data Science"]
image: https://www.vidyasource.com/img/courses/spark.jpg
---

# Data Engineering with Spark

> Master data engineering with Apache Spark through Vidya's hands-on training course. Learn to build scalable, fault-tolerant data pipelines, process big data, and leverage Spark's powerful features for real-world data engineering challenges.

- Canonical page: https://www.vidyasource.com/courses/data-engineering-with-spark/
- Structured data (JSON-LD): https://www.vidyasource.com/courses/data-engineering-with-spark.json
- Topics: Data Science
- Category: Data Science
- Instructor: Neil Chaudhuri, President
- Duration: About 8 hours total across two lessons of roughly 4 hours each. Run them on separate days or pair them into one intensive day.

## Syllabus

- Lesson 1: Mastering the Spark API (4 hours): Learn just enough Scala to write your own Spark jobs and navigate the ecosystem with confidence.
  - MapReduce: The Phantom Menace
  - Advantages of Spark
  - Just Enough Scala
  - Using the Spark Shell
  - Writing You Own Spark Jobs
  - The Spark Ecosystem
- Lesson 2: Professional Spark (4 hours): Test, optimize, secure, and deploy Spark on Docker and Kubernetes like a professional.
  - Just Enough Hadoop
  - Testing Your Spark Jobs
  - Optimizing Spark and When to Stop Trying
  - Spark on Docker
  - Deploying Spark to Kubernetes
  - Spark Security
  - Visualizing Your Spark Jobs

## From the instructor

> I have built several Scala and Spark applications currently in production and I worked with the original Spark team, AMPLab at UC Berkeley, on a research project for DARPA known as XDATA. Somehow I have helped enough developers around the world to earn Spark and Scala badges on Stack Overflow. I am passionate about Spark and look forward to helping you harness its power.

## Description

Apache Spark gets your analytics developed fast and running fast, but large-scale distributed computing is hard. You cannot set a breakpoint on code spread across a cluster, so monitoring and optimization matter, and you have to rethink architecture, security, and engineering practices like testing and DevSecOps.

Data Engineering with Spark teaches you just enough Scala to build powerful pipelines into your existing architecture, and to give those pipelines the same testing, continuous integration, containerization, and security as the rest of your enterprise.

### What makes this course different

Spark is a huge topic, and the typical course crams in too much too fast. You leave overwhelmed, and you never touch the architectural patterns and software engineering that separate a garage experiment from production architecture.

We take a practical approach. Rich code examples give you deep insight into the API, and the exercises use real datasets from Data.gov and encourage you to collaborate with your peers, the Spark Scaladoc, generative AI, and other sources just as you would at work. We also help you decide where to configure Spark yourself and where to hand configuration to a provider so you can focus on what matters.

Agile development and DevSecOps build quality in through automation, testing, and continuous delivery, and a distributed environment makes them even more valuable. Data Engineering with Spark shows you how to apply these techniques to improve the quality and reliability of your analytics.

---

Vidya is a certified small business in Northern Virginia that modernizes legacy systems, builds enterprise AI, and designs cloud and data architecture for commercial companies and federal agencies. Vidya documents its delivered engagements in case studies and publishes courses, tutorials, and articles for engineers and the people who lead them. The company name is Vidya. Its website is vidyasource.com. Start at https://www.vidyasource.com/llms.txt for the index of everything Vidya publishes, or https://www.vidyasource.com/contact/ to talk to Vidya.