Data Pipelines Courses and Certifications

PyCon US

Testing Data Pipelines - Techniques for Ensuring Data Flow Integrity

Explore effective techniques for testing data pipelines, ensuring smooth data flow and quick problem resolution. Learn about unit, integration, and end-to-end tests, plus unique methods like data snapshot testing.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

The Data Pipelines Behind Forest Carbon Credits - Why Pachama Uses Flyte to Orchestrate Workflows

Explore how Pachama uses Flyte to manage complex data and ML pipelines for transparent forest carbon credit computation, including workload management, configuration, and lessons learned.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

AICamp

The Fundamentals of Type-safe, Reproducible, and Scalable Data Pipelines

Master the fundamentals of building robust data science and ML pipelines using Flytekit, focusing on type safety, reproducibility, and scalability through Docker containerization and Python-based task optimization.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

PyCon US

Building Resilient Data Pipelines - The Power of Idempotency

Discover how to build resilient data pipelines in Python using idempotency principles, exploring design patterns, testing strategies with pytest, and avoiding common pitfalls.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

StreamNative

Truly Scalable Operational Data Layers for Data Pipelines

Discover how to build and scale operational data layers effectively, focusing on source-to-destination streaming systems and achieving true scalability for large-scale data processing needs.

• YouTube
• 15 minutes
• Self-Paced
• Free Video

Serverless Data Processing with Dataflow: Develop Pipelines

Develop data pipelines with Apache Beam and Dataflow. Cover transforms, windowing, I/O connectors, schemas, state APIs, Beam SQL, and notebooks.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Coursera

Trace and Fix Data Anomalies

Master systematic root cause analysis to trace data anomalies through pipelines, implement resolution strategies, and maintain reliable automated workflows with hands-on debugging techniques.

• Coursera
• 1 hour 29 minutes
• Self-Paced
• Paid Course

Coursera

Engineer, Validate, and Govern ML Data

Master ML data pipeline engineering with ETL workflows, data quality validation, and governance using Airflow and Spark for production-ready systems.

• Coursera
• 2 hours 29 minutes
• Self-Paced
• Paid Course

Coursera

Technology & Project Enablement

Explore the technical side of people analytics, covering HRIS data management, CSV preparation, project planning, and building an end-to-end analytics pipeline for HR professionals.

• Coursera
• 7 hours
• Self-Paced
• Paid Course

The Path to Insights: Data Models and Pipelines

716 ratings at Coursera

Explore data modeling, databases, and ETL processes to extract, transform, and load data for effective business intelligence. Learn to design efficient data pipelines and optimize BI processes.

• Coursera
• 16 hours 56 minutes
• Self-Paced
• Paid Course

Explore how QRadar processes events through its data pipeline, from raw data normalization at Event Collector level to rule testing and storage at Event Processor level.

• IBM Training
• 1 hour
• Self-Paced
• Free Online Course

Coursera Career Certificate

Building Smarter Data Pipelines: SQL, Spark, Kafka & GenAI

99 ratings at Coursera

Master scalable data engineering with SQL, Spark, Kafka & GenAI through hands-on projects that mirror real-world enterprise challenges and cutting-edge technologies.

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

Coursera

Data Engineering: Pipelines, ETL, Hadoop

12 ratings at Coursera

Master data engineering: build robust pipelines, implement ETL processes, and handle large datasets with Hadoop. Gain expertise in extracting, transforming, and loading data for efficient processing and analysis.

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

Coursera

Engineering Data Ecosystems: Pipelines, ETL, Spark

10 ratings at Coursera

Explore data ecosystems, pipelines, ETL processes, and Apache Spark for big data handling. Gain essential skills for modern data engineering and large-scale data processing.

• Coursera
• 2 hours 41 minutes
• Self-Paced
• Paid Course

Coursera

Building Automated Data Pipelines with Spark,dbt,and Airflow

Master building production-ready data pipelines using Apache Spark, dbt, and Airflow to process millions of records, integrate diverse sources, and automate workflows with monitoring and retry logic.

• Coursera
• 8 hours 32 minutes
• Self-Paced
• Paid Course