Free Udemy Course: Google Cloud Professional Data Engineer 2025 PRACTICE EXAM

OverviewThis course is designed to help learners master the skills and knowledge required to become a Google Cloud Professional Data Engineer. You will learn how to design, build, secure, and operationalize data processing systems on Google Cloud, while preparing to pass the Professional Data Engineer certification exam with confidence.Through a mix of conceptual lessons, hands-on labs, case studies, and exam-focused strategies, learners will gain the ability to manage end-to-end data solutions — from ingestion and transformation to storage, analytics, and machine learning integration.What You Will LearnBy the end of this course, you will be able to:Design and implement data processing systems that are secure, reliable, and scalable.Ingest, process, and transform data using services like Pub/Sub, Dataflow, Dataproc, and Data Fusion.Store and manage data using Google Cloud’s storage solutions, including BigQuery, Spanner, Bigtable, and Cloud Storage.Prepare data for analytics and machine learning, enabling advanced use cases with BigQuery, Dataplex, and Vertex AI.Optimize, automate, and monitor workloads, applying cost-saving strategies and fault tolerance mechanisms.Apply exam strategies and practice with real-world scenarios to succeed in the Professional Data Engineer certification exam.Course ModulesModule 1: Introduction to Google Cloud & Data EngineeringRole of a Professional Data EngineerCertification overview & exam structureCore principles of data engineeringModule 2: Designing Data Processing SystemsSecurity, compliance, and governanceReliability, fidelity, and disaster recoveryMigration strategies and architecture designModule 3: Ingesting & Processing DataBatch vs. streaming data pipelinesTools: Dataflow, Pub/Sub, Dataproc, Data Fusion, KafkaCI/CD and pipeline orchestration (Cloud Composer, Workflows)Module 4: Storing & Managing DataData warehouse design with BigQueryData lakes with Dataplex and Cloud StorageData mesh and federated governanceModule 5: Preparing Data for Analytics & MLQuery optimization and BigQuery advanced featuresData sharing with Analytics HubPreparing datasets for ML pipelines (Vertex AI)Module 6: Automating & Optimizing WorkloadsMonitoring and troubleshooting with Cloud Logging & MonitoringAutomation with Composer DAGs and WorkflowsResource optimization & cost managementModule 7: Exam Preparation & PracticeSample exam questions and scenario walkthroughsStudy strategies & time managementFinal mock test with detailed feedbackWho This Course Is ForData engineers, analysts, and architects aspiring to become Google Cloud certified.Cloud professionals seeking to expand their expertise in data processing and analytics.Developers and IT specialists transitioning into data engineering roles.Learners preparing specifically for the Professional Data Engineer certification exam.