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

Preparing for Google Cloud Certification: Cloud Data Engr Professional Certificate

Advance your career in data engineering

Included with Coursera Plus

Earn a career credential that demonstrates your expertise
4.6

(7,128 reviews)

Intermediate level

Recommended experience

Flexible schedule
4 weeks at 10 hours a week
Learn at your own pace
Earn a Certificate
With paid plans
Earn a career credential that demonstrates your expertise
4.6

(7,128 reviews)

Intermediate level

Recommended experience

Flexible schedule
4 weeks at 10 hours a week
Learn at your own pace
Earn a Certificate
With paid plans

What you'll learn

  • Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud.

  • Employ BigQuery to carry out interactive data analysis.

  • Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.

  • Choose between different data processing products on Google Cloud.

Details to know

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Taught in English
Recently updated!

October 2025

29 practice exercises

See how employees at top companies are mastering in-demand skills

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Professional Certificate - 5 course series

What you'll learn

  • Differentiate between data lakes and data warehouses.

  • Explore use-cases for each type of storage and the available data lake and warehouse solutions on Google Cloud.

  • Discuss the role of a data engineer and the benefits of a successful data pipeline to business operations.

  • Examine why data engineering should be done in a cloud environment.

Skills you'll gain

Google Cloud Platform, Data Warehousing, Cloud Storage, Data Lakes, Data Processing, Scalability, Data Infrastructure, Cloud Engineering, Big Data, SQL, and Data Pipelines

What you'll learn

  • Review different methods of data loading: EL, ELT and ETL and when to use what

  • Run Hadoop on Dataproc, leverage Cloud Storage, and optimize Dataproc jobs

  • Build your data processing pipelines using Dataflow

  • Manage data pipelines with Data Fusion and Cloud Composer

Skills you'll gain

Data Pipelines, Apache Spark, Google Cloud Platform, Extract, Transform, Load, Data Transformation, Apache Hadoop, Data Processing, Apache Airflow, Big Data, Data Integration, Serverless Computing, and Data Migration

What you'll learn

  • Ingest and manage streaming data using Pub/Sub and Managed Service for Apache Kafka

  • Build and deploy streaming data pipelines with Dataflow

  • Implement streaming data solutions for real-time analytics and application serving with BigQuery and Bigtable

Skills you'll gain

Performance Tuning, Data Processing, Dataflow, Data Pipelines, Google Cloud Platform, Serverless Computing, Real Time Data, Big Data, Scalability, Applied Machine Learning, Extract, Transform, Load, and SQL

What you'll learn

  • Differentiate between ML, AI and deep learning.

  • Discuss the use of ML API’s on unstructured data.

  • Execute BigQuery commands from notebooks.

  • Create ML models by using SQL syntax in BigQuery and without coding using Vertex AI AutoML.

Skills you'll gain

Google Cloud Platform, Applied Machine Learning, Machine Learning, Jupyter, Unstructured Data, Data Pipelines, Tensorflow, Artificial Intelligence, MLOps (Machine Learning Operations), and Big Data

What you'll learn

  • List the domains covered on the Professional Data Engineer (PDE) certification exam.

  • Identify gaps in your knowledge and skills for each domain.

Skills you'll gain

Data Storage, Data Processing, Google Cloud Platform, Data Management, Data Pipelines, Data Analysis, Automation, Data Security, Data Infrastructure, Cloud Storage, and Data Maintenance

Earn a career certificate

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Instructor

Google Cloud Training
Google Cloud
1,996 Courses3,646,892 learners

Offered by

Google Cloud

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