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Data Engineering with AWS Machine Learning

3.7(34)
Intermediate 2.9 hours English Professional Certificate

About this course

This course focuses specifically on the data engineering layer that feeds AWS machine learning workflows: choosing between storage options, comparing database services, using data warehouses and data lakes as ML repositories, streaming versus batch ingestion, and transforming raw data with AWS Data Pipeline, Apache Spark on EMR, or serverless AWS Glue and Athena.

The honest take: at 34 reviews and 3.7 stars, this is a niche, lower-rated course relative to Pluralsight's broader catalog — it's narrowly scoped to the AWS data engineering side of ML (not model building itself), which makes it useful specifically for engineers responsible for getting data ML-ready, but it's not a general data engineering or ML course.

What you'll learn

Choose appropriate AWS data storage options for machine learning workloads
Compare AWS database services as ML data repositories
Use data warehouses and data lakes for ML data preparation
Apply streaming and batch data ingestion approaches on AWS
Transform data using AWS Data Pipeline, Apache Spark on EMR, and serverless Glue/Athena

This course includes

2.9h
On-demand video
Yes
Mobile access
English
Language
Comparison · LBS

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Prices & availability can change — confirm on the provider's site. We're not affiliated with any single provider.

Instructor

KS
Kim Schmidt
Pluralsight instructor
— learners— courses — instructor rating

Kim Schmidt is an AWS Partner and Vendor instructor with prior experience at Dun & Bradstreet, Google, Microsoft, and AWS.

Requirements

  • Basic familiarity with AWS services is helpful

Who this course is for

  • Data engineers responsible for preparing data for AWS ML pipelines
  • Cloud practitioners narrowly focused on the AWS data layer for machine learning

About this provider

PL
Pluralsight
Tech skills platform for software developers, IT ops, and security professionals.
4.4 trust score
Visit Pluralsight →

Frequently asked questions

No — it focuses specifically on the data engineering layer (storage, ingestion, transformation) that feeds ML workflows, not model training itself.
3.7 stars from 34 reviews — lower than most other Pluralsight courses in this catalog, worth weighing against the narrow scope.
Yes — it was last updated in February 2025.
AWS Data Pipeline, Apache Spark on Amazon EMR, and serverless AWS Glue with Amazon Athena.
2 hours 55 minutes across 13 modules.
Paid
Pluralsight subscription · from $21/mo billed annually (free trial)
View on Pluralsight