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

Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate

Advance your career in data engineering

100,132 already enrolled

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Earn a career credential that demonstrates your expertise
4.6

(7,062 reviews)

Intermediate level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace
Earn a career credential that demonstrates your expertise
4.6

(7,062 reviews)

Intermediate level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace

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

Shareable certificate

Add to your LinkedIn profile

Industry certification
Taught in English

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.

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

What you'll learn

  • Interpret use-cases for real-time streaming analytics.

  • Manage data events using the Pub/Sub asynchronous messaging service.

  • Write streaming pipelines and run transformations where necessary.

  • Interoperate Dataflow, BigQuery and Pub/Sub for real-time streaming and analysis

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.

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.

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Google Cloud Training
Google Cloud
1,747 Courses3,089,216 learners

Offered by

Google Cloud

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Frequently asked questions

¹ Median salary and job opening data are sourced from Lightcast™ Job Postings Report. Content Creator, Machine Learning Engineer and Salesforce Development Representative (1/1/2024 - 12/31/2024) All other job roles (3/1/2024 - 3/1/2025)