GOOGLE CLOUD CERTIFIED PROFESSIONAL DATA ENGINEER (PDE)
The Google Cloud Certified Professional Data Engineer (PDE) course prepares learners to design, build, operationalize, secure, and monitor data processing systems on Google Cloud Platform (GCP). The course focuses on transforming raw data into actionable insights by applying data engineering best practices, scalable architectures, and analytics solutions. Learners will gain hands-on experience designing data pipelines, managing large-scale datasets, implementing machine learning workflows, and ensuring data quality, security, and reliability. This course equips participants with the skills required for data-driven decision-making and prepares them for the Google Cloud Professional Data Engineer certification. Course Objectives By the end of this course, learners will be able to: Design and implement scalable data processing architectures on Google Cloud Build and manage batch and real-time data pipelines Store, process, and analyze structured and unstructured data Apply data governance, security, and compliance best practices Optimize data workflows for performance, reliability, and cost Integrate machine learning models into data solutions Monitor and maintain production data systems
Course Curriculum
1
- Role of a data engineer
- Data engineering lifecycle
- Overview of Google Cloud data and analytics services
- Data architectures and design patterns
2
- Relational and non-relational data storage
- Data warehouses and data lakes
- Managing structured, semi-structured, and unstructured data
- Data modeling and schema design
3
- Batch and stream processing concepts
- Designing ETL and ELT pipelines
- Workflow orchestration and scheduling
- Ensuring data reliability and fault tolerance
4
- Streaming data architectures
- Event-driven data ingestion
- Real-time analytics and dashboards
- Handling late and out-of-order data
5
- Integrating machine learning into data pipelines
- Feature engineering and data preparation
- Model deployment and monitoring
- Using analytics for predictive insights
6
- Data access control and encryption
- Data governance and lifecycle management
- Compliance standards and regulatory requirements
- Data loss prevention and auditing
7
- Monitoring data pipelines and workloads
- Performance tuning and scalability
- Cost optimization strategies
- Troubleshooting and incident management
8
- Real-world data engineering use cases
- Hands-on labs and practical exercises
- Review of certification exam domains
- Best practices for exam success
9
- Data engineers
- Data analysts and scientists
- Cloud engineers and architects
- Business intelligence professionals
- IT professionals preparing for the Google Cloud PDE certification
10
- Understanding of cloud computing fundamentals
- Basic knowledge of databases and SQL
- Familiarity with data processing concepts
- Prior experience with Google Cloud is recommended
11
- Assessment Methods
- Practical labs and assignments
- Quizzes and knowledge checks
- Final assessment or certification-oriented evaluation
12
- Instructor-led training
- Hands-on labs and practical demonstrations
- Case studies and real-world data scenarios
13
- This course prepares participants for the Google Cloud Certified Professional Data Engineer (PDE) certification exam
14
- Comprehensive training materials
- Hands-on lab guides
- Practice exam questions
- Certificate of course completion
This course includes
- 14+ Activity Modules
- 40 hours + lessons
- Lifetime access
- Certificate of completion
- Available on desktop and mobile
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