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Data Engineering for AI and ML Pipelines

Name: Data Engineering for AI and ML Pipelines
Price: 49 USD
Availability: InStock

About this course

Data Engineering for AI and ML Pipelines equips you with the skills to build the data infrastructure that powers modern machine learning systems on Databricks. Across three courses, you will progress from foundational data engineering with Apache Spark and PySpark, through Delta Lake and Medallion Architecture pipelines, to feature engineering and feature stores that supply clean, AI-ready data directly to ML workflows. By the end of this specialization, you will be able to design end-to-end data pipelines using Bronze, Silver, and Gold layers, enforce schema and data quality at scale, build and query feature stores for both structured and text/embedding data, and automate pipeline orchestration using Databricks Jobs and MLflow. This specialization is ideal for aspiring data engineers, machine learning engineers, and data professionals who want to master the full journey from raw data to ML-ready features.

75/100

CourseAsk score

What the provider tells you: 39/45
Who stands behind it: 20/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

design end-to-end data pipelines
enforce schema and data quality at scale
build and query feature stores
automate pipeline orchestration using Databricks Jobs and MLflow

Course objectives

teach foundational and advanced data engineering skills
prepare participants for roles in data engineering and machine learning

Machine Learning #apache spark #pyspark #mlops #data pipelines #data quality #feature engineering #delta lake #databricks #medallion architecture #ml workflows #feature stores

$49.00

Price shown by Coursera — confirm on their site.

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