Data Engineering Courses and Certifications

Pragmatic AI Labs

Scripting with Python and SQL for Data Engineering

Master data manipulation using Python and SQL for data engineering. Extract, transform, and load data efficiently to drive insights and decision-making.

• edX
• 4 weeks, 3-6 hours/week
• Self-Paced
• Free Online Course (Audit)

LearnKartS

Data Engineering Foundations on AWS

Discover AWS data engineering fundamentals through hands-on experience with S3, EBS, EFS, ETL pipelines, SQL, and data modeling to build job-ready cloud skills for in-demand roles.

• Coursera
• 5 hours 21 minutes
• Self-Paced
• Paid Course

Pragmatic AI Labs

Advanced Data Engineering

Become an expert in scaling data systems. Master Celery, Airflow, graph databases. Build real-world solutions for massive datasets and complex workflows. Optimize performance at enterprise scale. 10 hands-on labs and exercise to "learn by doing".

• edX
• 4 weeks, 3-6 hours/week
• Self-Paced
• Free Online Course (Audit)

Packt

Introduction to Data Engineering on AWS

Master AWS Glue and Redshift to build scalable ETL pipelines, optimize data warehousing, and transform raw data into actionable insights for modern cloud-based analytics workflows.

• Coursera
• 8 hours 25 minutes
• Self-Paced
• Paid Course

Packt Credential

Data Engineering on AWS - The Complete Training

Master AWS data engineering by building scalable pipelines, processing big data with EMR, streaming with Kinesis, and creating data lakes using Glue, Redshift, and other key services.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Coursera Credential

Open source Data Engineering with Spark, dbt & Airflow

Master open-source data engineering using Apache Spark, dbt, and Airflow to build scalable pipelines, optimize performance, and deploy CI/CD workflows for production-ready data infrastructure.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 6 courses

Pragmatic AI Labs

Cloud Data Engineering

Master data engineering for cloud-native applications through distributed systems, big data, and serverless technologies.

• edX
• 4 weeks, 3-6 hours/week
• Self-Paced
• Free Online Course (Audit)

Pragmatic AI Labs

Data Engineering with Delta Lake on Databricks

Master production-ready data pipelines using Delta Live Tables and Medallion Architecture on Databricks through hands-on labs and a complete inventory management capstone project.

• Coursera
• 5 hours 9 minutes
• Self-Paced
• Paid Course

Pragmatic AI Labs

Web Applications and Command-Line Tools for Data Engineering

Learn to build web apps, microservices, and command-line tools for efficient data engineering using Python, FastAPI, and Rust.

• edX
• 4 weeks, 3-6 hours/week
• Self-Paced
• Free Online Course (Audit)

KodeKloud

Data Engineering Essentials

Master MLOps-ready data engineering with Kafka, Spark, and Airflow to build scalable, automated pipelines that bridge raw data to production AI systems.

• Coursera
• 5 hours 27 minutes
• Self-Paced
• Paid Course

Coursera Credential

Level Up: Advanced SQL for Data Engineering

Master advanced SQL skills for data engineering, covering ELT pipelines, lakehouse architecture, performance optimization, security, and data governance to excel in senior engineering roles.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 5 courses

Coursera Credential

Modern Data Architecture & Lakehouse Engineering

Discover how to architect production-ready lakehouse platforms combining data lakes and warehouses with hands-on training in Spark, dbt, Airflow, and cloud infrastructure optimization.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 2 courses

Coursera Credential

Pipeline Architects: Data Engineering to Lakehouse

Master end-to-end data engineering, from ingestion to lakehouse delivery, using Python, SQL, Airflow, dbt, Snowflake, Kafka, and Delta Lake to build production-ready pipelines at enterprise scale.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 10 courses

Coursera

Data Engineering & Pipeline Reliability for Machine Learning

Master data engineering skills using Python and pandas to clean, encode, validate datasets, build ML pipelines, manage schema changes, and optimize compute costs for production-ready ML infrastructure.

• Coursera
• 9 hours 3 minutes
• Self-Paced
• Paid Course

Coursera

Strategize Your Data Engineering Evolution

Elevate your data engineering expertise by mastering architecture gap analysis, SQL-driven cost-benefit models, and strategic migration roadmaps to lead enterprise-wide modernization initiatives.

• Coursera
• 2 hours 11 minutes
• Self-Paced
• Paid Course