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Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate

An intensive, lab-rich Professional Certificate that equips learners for the Google Data Engineer role—with strong exam alignment and real GCP experience.

access

Lifetime

level

Medium

certificate

Certificate of completion

language

English

What will you learn in Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate Course

  • Design, build, and maintain data processing systems on GCP, including BigQuery, Cloud Storage, Dataproc, and Pub/Sub.

  • Develop batch and streaming ETL pipelines and data warehouse solutions at scale.

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  • Use machine learning tools and fundamentals to create ML-based analytics applications.

  • Optimize performance, security, and reliability of data systems in production environments.

Program Overview

Module 1: Big Data & Machine Learning Fundamentals

⏳ ~4 weeks (5 hr/week)

  • Topics: Core GCP data and ML services; big data architectures.

  • Hands-on: Qwiklabs on BigQuery, Cloud Storage, and machine learning pipelines.

Module 2: Modernizing Data Lakes and Warehouses

⏳ ~4 weeks

  • Topics: Data lake vs warehouse, ingestion strategies, management patterns.

  • Hands-on: ETL pipelines with Cloud Storage, BigQuery, Dataproc.

Module 3: Building Batch Data Pipelines

⏳ ~4 weeks

  • Topics: Orchestration with Dataflow, scheduling, error handling.

  • Hands-on: Build scalable batch pipelines in Qwiklabs.

Module 4: Streaming Analytics Systems

⏳ ~4 weeks

  • Topics: Real-time ingestion with Pub/Sub, Dataflow streaming, windowing.

  • Hands-on: Create live streaming ETL jobs.

Module 5: Smart Analytics, Machine Learning & AI

⏳ ~4 weeks

  • Topics: ML model deployment, inference pipelines, AI integration.

  • Hands-on: Setup ML workflows in Qwiklabs and use AI APIs.

Module 6: Preparing for the Professional Data Engineer Journey

⏳ ~4 weeks

  • Topics: Prepare study plans, exam domains, mock questions.

  • Hands-on: Diagnostic quizzes, create a personalized study plan.

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Job Outlook

  • This certificate prepares learners for roles such as Cloud Data Engineer, Data Architect, and ML Engineer on GCP.

  • Median completion time is ~3.5 months at 5 hours/week, aligning with industry expectations.

  • Graduates gain hands-on experience using real GCP services; professional Data Engineer roles are among the top‑paying cloud certifications.

9.7Expert Score
Highly Recommendedx
This intermediate-level certificate offers comprehensive, lab-based training tailored to the Professional Data Engineer exam and real-world use cases.
Value
9
Price
9.2
Skills
9.4
Information
9.5
PROS
  • Deep, hands-on Qwiklabs experience across core GCP data services.
  • Directly aligned with the Google Data Engineer certification exam.
  • Google Cloud–produced content with expert instructors and real use cases.
CONS
  • GCP-specific—limited cross-cloud skills.
  • Requires prior experience (SQL, ETL, Python); may overwhelm true beginners.

Specification: Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate

access

Lifetime

level

Medium

certificate

Certificate of completion

language

English

Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate
Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate
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