GCP Professional Data Engineer

4865 Ratings (4.8)

A Professional Data Engineer enables data-driven decision making by collecting, transforming, and publishing data. A Data Engineer should be able to design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A Data Engineer should also be able to leverage, deploy, and continuously train pre-existing machine learning models.

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About the course

A Professional Data Engineer enables data-driven decision making by collecting, transforming, and publishing data. A Data Engineer should be able to design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A Data Engineer should also be able to leverage, deploy, and continuously train pre-existing machine learning models.

Course Contents

Designing data processing systems

Selecting the appropriate storage technologies
  • Mapping storage systems to business requirements
  • Data modeling
  • Tradeoffs involving latency, throughput, transactions
  • Distributed systems
  • Schema design
Designing data pipelines
  • Data publishing and visualization (e.g., BigQuery)
  • Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
  • Online (interactive) vs. batch predictions
  • Job automation and orchestration (e.g., Cloud Composer)
Designing a data processing solution
  • Choice of infrastructure
  • System availability and fault tolerance
  • Use of distributed systems
  • Capacity planning
  • Hybrid cloud and edge computing
  • Architecture options (e.g., message brokers, message queues, middleware, service-oriented architecture, serverless functions)
  • At least once, in-order, and exactly once, etc., event processing
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Course Prerequisites

  • If you’re already a data scientist, a data engineer, data analyst, machine learning engineer or looking for a career change into the world of data, the Google Cloud Professional Data Engineer Certification is for you
  • Being able to use cloud technologies is becoming a requirement for any kind of data focused role
  • Learners should be familiar with the fundamentals of cloud computing and relevant practical experience

Who should attend?

  • Google recommends 3+ years of industry experience and 1+ years designing and managing solutions using GCP for professional level certifications
  • Data professionals

Number of Hours: 40hrs

Certification

GCP Professional Cloud Collaboration Engineer (GCP PDE )

Keyfeatures

  • One to One Training
  • Online Training
  • Fastrack & Normal Track
  • Resume Modification
  • Mock Interviews
  • Video Tutorials
  • Materials
  • Real Time Projects
  • Virtual Live Experience
  • Preparing for Certification

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TechyEdz Software Specialization in developing customized suite of HR consulting solutions based on the operational models of our clients with a special focus on small & Large Enterprises. We bring practical, results driven HR Practice to our clients business that would help them retain people, Improve business productivity and performance of employee.