Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate

This Labor Day, enjoy $120 off Coursera Plus. Unlock access to 10,000+ programs. Save today.

Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate

Advance your career in data engineering

Instructor: Google Cloud Training

103,052 already enrolled

Included with Coursera Plus

Learn more

5 course series

Earn a career credential that demonstrates your expertise

4.6

(7,114 reviews)

Intermediate level

Recommended experience

4 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 course series

Earn a career credential that demonstrates your expertise

4.6

(7,114 reviews)

Intermediate level

Recommended experience

4 weeks to complete

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.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Industry certification

Taught in English

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

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Professional Certificate - 5 course series

Google Cloud Professional Data Engineer certification was ranked #1 on Global Knowledge's list of 15 top-paying certifications in 2021! Enroll now to prepare!

---

87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to advance your career and provides training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer certification.

Here's what you have to do

1) Complete the Coursera Data Engineering Professional Certificate

2) Review other recommended resources for the Google Cloud Professional Data Engineer certification exam

3) Review the Professional Data Engineer exam guide

4) Complete Professional Data Engineer sample questions

5) Register for the Google Cloud certification exam (remotely or at a test center)

Applied Learning Project

This professional certificate incorporates hands-on labs using Qwiklabs platform.These hands on components will let you apply the skills you learn. Projects incorporate Google Cloud Platform products used within Qwiklabs. You will gain practical hands-on experience with the concepts explained throughout the modules.

Applied Learning Project

This Professional Certificate incorporates hands-on labs using our Qwiklabs platform.

These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google BigQuery, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.

Modernizing Data Lakes and Data Warehouses with Google Cloud

Course 18 hours

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

Category: Google Cloud Platform

Category: Data Warehousing

Category: Data Lakes

Category: Data Transformation

Category: Cloud Storage

Category: Data Pipelines

Category: SQL

Category: Cloud Engineering

Category: Data Infrastructure

Category: Data Processing

Category: Big Data

Category: Scalability

Building Batch Data Pipelines on Google Cloud

Course 217 hours

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

Category: Data Pipelines

Category: Google Cloud Platform

Category: Apache Spark

Category: Data Processing

Category: Extract, Transform, Load

Category: Data Transformation

Category: Apache Hadoop

Category: Apache Airflow

Category: Data Migration

Category: Serverless Computing

Category: Big Data

Category: Data Integration

Building Resilient Streaming Analytics Systems on Google Cloud

Course 38 hours

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

Skills you'll gain

Category: Performance Tuning

Category: Data Processing

Category: Google Cloud Platform

Category: Data Pipelines

Category: Real Time Data

Category: Analytics

Category: Scalability

Category: SQL

Category: Big Data

Category: Data Transformation

Smart Analytics, Machine Learning, and AI on Google Cloud

Course 46 hours

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

Category: Google Cloud Platform

Category: Applied Machine Learning

Category: Machine Learning

Category: Jupyter

Category: Unstructured Data

Category: Tensorflow

Category: Natural Language Processing

Category: Data Pipelines

Category: MLOps (Machine Learning Operations)

Category: Big Data

Category: Artificial Intelligence and Machine Learning (AI/ML)

Preparing for your Professional Data Engineer Journey

Course 54 hours

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

Category: Data Storage

Category: Data Processing

Category: Google Cloud Platform

Category: Data Security

Category: Data Warehousing

Category: Data Management

Category: Automation

Category: Data Analysis

Category: Data Migration

Category: Data Pipelines

Category: Data Maintenance

Category: Data Integration

Category: Data Infrastructure

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

1,934 Courses3,571,858 learners

Offered by

Google Cloud

Why people choose Coursera for their career

Felipe M.

Learner since 2018

"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020

"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021

"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Open new doors with Coursera Plus

Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Learn more

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Explore degrees

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Learn more

Frequently asked questions

This Professional Certificate is designed to be completed in three and a half months at five hours per week.

One (1) year of experience with one or more of the following:

• A common query language such as SQL

• Extract, transform, load activities

• Data modeling

• Machine learning and/or statistics

• Programming in Python

We strongly recommend you take these courses in order, beginning with Big Data and Machine Learning Fundamentals. This is especially important when completing the Qwiklabs projects, as these hands-on labs build upon the work you complete in preceding courses.