Build your expertise in data engineering on Google Cloud with the Data Engineer professional certificate, developed by Google Cloud and delivered on edX.
This program teaches you the fundamental principles and applications of big data and machine learning (ML) products within Google Cloud, preparing you for a role as a professional data engineer.
The program is delivered through six hands-on courses:
- Introduction to Data Engineering on Google Cloud
- Serverless Data Processing with Dataflow: Foundations
- Serverless Data Processing with Dataflow: Develop Pipelines
- Serverless Data Processing with Dataflow: Operations
- Boost Productivity with Gemini in BigQuery
- Work with Gemini Models in BigQuery
Prepare for professional data engineer certification. Create a personalized study plan, explore exam topics, and assess your readiness for the PDE certification exam.
Understand the role of a data engineer on Google Cloud. Learn the key responsibilities of data engineers, how those align with Google Cloud offerings, and strategies for addressing common data engineering challenges.
Design and optimize robust batch data pipelines. Discover how to build and optimize reliable batch data pipelines on Google Cloud, practicing with Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless), and ensuring data quality, monitoring, and alerting.
Learn the foundations of serverless data processing. Deepen your knowledge of Apache Beam, explore the benefits of the Beam Portability framework, and learn to apply the right security model for your Dataflow pipelines.
Develop advanced dataflow pipelines. Learn streaming data concepts like windows, watermarks, and triggers, using State and Timer APIs for stateful transformations, and utilizing Beam notebooks for iterative development.
Manage and operate dataflow pipelines for stability and resilience. Explore the Dataflow operational model, examine tools for troubleshooting and optimizing performance, and review best practices for testing, deployment, and reliability.
Boost data practitioner productivity with Gemini in BigQuery. Expedite your development pipeline by exploring the suite of AI-driven features in Gemini in BigQuery for data exploration, preparation, code generation, troubleshooting, and workflow visualization.
Implement Generative AI solutions using Gemini models in BigQuery. Learn the workflow for solving business problems with Gemini models, including practical use cases like customer relationship management, and receive step-by-step guidance using SQL and Python notebooks.
By completing all eight courses, you'll gain a firm understanding of big data and ML principles and applications on Google Cloud, empowering you to confidently design and manage comprehensive data architectures.
