
MICRO DEGREE
Google Cloud Professional Data Engineer Certification
Certified Google Cloud Professional Data Engineer
100% LIVE Interactive Classes
Certified Google Cloud Professional Data Engineer

100% LIVE Interactive Classes
Reserve your spot today!
Basic Info
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Application closes on:20 May 2026
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What is in it for you?
100% Live Classes
Instructor-led Live Sessions
Attend 4 weeks of instructor led live classes from the top 1% industry experts
Projects & Case Studies
Projects & Case Studies
Gain hands-on experience with projects and real-world case studies for impactful learning.
Verified Certificate
Verified Certificate
Earn a industry recognized certificate and kick start your career
Session Recordings
Session Recordings
Revisit older chapters anytime with recorded sessions
Flexible Schedule
Flexible Schedule
Choose live classes from different cohorts that fit your availability.
Hands-on Classes
Hands-on Classes
Hands-on classes to enhance your learning experience
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Reserve your spot today!
Basic Info
Select Offers
Application closes on:20 May 2026
Get instant access of pre-course material!
Talk to Us
We’re here to help! Reach us at:
Learn from Top 1%
Sr. Managers, VPs, CXOs, Directors & Founders from companies shaping the future.

Curriculum
Duration: 4 weeks
Max Batch Size: 15 persons
Live Sessions Schedule
Sat - Sun (Weekends Only)
Timing 7:00 AM - 9:00 AM / 8:30 AM - 10:30 AM / 11:00 AM - 1:00 PM / 5:00 PM - 7:00 PM / 7:30 PM - 9:30 PM EST
- Overview of Google Cloud Platform (GCP)
- Role of a Data Engineer in GCP Ecosystem
- Core GCP Services for Data Engineering
- Understanding the Google Cloud Certification Path
- Key Responsibilities of a Google Cloud Data Engineer
- Introduction to Professional Data Engineer Exam
Mentors

20+ Years, Sr. Director, PayTm
Course Includes

LIVE Interactive Sessions

Quizzes, Assignments & Projects

Study Materials & Session Recordings

Certificate
Tools Covered
Course Includes

LIVE Interactive Sessions

Quizzes, Assignments & Projects

Study Materials & Session Recordings

Certificate
Course Pre-requisites
Working knowledge of SQL for querying and manipulating relational data
Basic proficiency in Python programming
Fundamental understanding of cloud computing concepts (VMs, storage, networking)
Familiarity with data engineering concepts such as ETL, batch and streaming processing
Outcomes
Design and build scalable data pipelines on Google Cloud using Dataflow, Dataproc, and Pub/Sub
Implement data lake and data warehouse architectures using BigQuery and Cloud Storage
Develop ETL/ELT workflows for both batch and streaming data processing on GCP
Apply data governance, security, and compliance best practices using Data Catalog, IAM, and DLP API
Optimize data pipeline performance, cost efficiency, and reliability for production workloads
Build and deploy machine learning models using BigQuery ML and AI Platform
Analyse and monitor data systems using Cloud Monitoring, Logging, and Stackdriver
Prepare for and pass the Google Cloud Professional Data Engineer certification exam
Projects You Will Build
Practical, enterprise-grade projects that reflect real industry challenges
Retail Sales Analytics Pipeline
Build an end-to-end batch and streaming data pipeline to ingest, transform, and analyze retail sales data. Use Cloud Storage for data lake ingestion, Pub/Sub and Dataflow for real-time event processing, and BigQuery as the data warehouse for analytical queries. Create dashboards in Looker Studio to surface business insights such as sales trends and inventory optimization.
IoT Sensor Data Platform
Design a real-time data platform to ingest and process IoT sensor data from thousands of connected devices. Leverage Pub/Sub for message ingestion, Dataflow for stream processing and windowed aggregations, and BigQuery for long-term analytics. Integrate BigQuery ML to build anomaly detection models that trigger predictive maintenance alerts.
Financial Fraud Detection System
Develop a secure, real-time data pipeline to detect fraudulent activities in financial transactions. Use Dataflow for streaming fraud scoring, BigQuery ML for training and deploying predictive classification models, and implement security controls using IAM roles and the Data Loss Prevention API. Apply data governance practices with Data Catalog to ensure compliance with financial regulations.

for successfully completing the 'Google Cloud Professional Data Engineer Certification' course conducted from 21 Apr 2026 to 19 May 2026
Add a Industry Recognized
Certificate To Your Resume
Industry Recognized
Certificate
Learn the best from the best

Career Advancements
Elevate your career with a respected certificate

Industry Respect
Gain credibility in the field

Networking
Connect with experts and peers

Opportunities
Attract exciting job prospects and promotions


for successfully completing the 'Google Cloud Professional Data Engineer Certification' course conducted from 21 Apr 2026 to 19 May 2026

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Frequently Asked Questions
Everything you need to know about the course
You should have working knowledge of SQL and Python, a basic understanding of cloud computing concepts, and some familiarity with data engineering fundamentals such as ETL processes and batch vs. streaming data. No prior Google Cloud experience is required, as the course covers GCP services from the ground up.
The curriculum covers designing data pipelines with Dataflow and Dataproc, messaging with Pub/Sub, data warehousing with BigQuery, data lake architecture with Cloud Storage, machine learning with BigQuery ML and AI Platform, data governance with Data Catalog and IAM, security with DLP API, and performance optimization for production workloads.
The course is designed to be completed in 4 weeks. You should plan to dedicate approximately 10-15 hours per week, which includes video lectures, hands-on labs, project work, and certification exam preparation.
You will complete three industry-relevant projects: a retail sales analytics pipeline, a real-time IoT sensor data platform, and a financial fraud detection system. Each project involves building end-to-end data solutions using core GCP services like Dataflow, Pub/Sub, BigQuery, and BigQuery ML.
This course prepares you for the Google Cloud Professional Data Engineer certification, one of the most sought-after cloud certifications in the industry. Completing the course and earning the certification qualifies you for roles such as Data Engineer, Big Data Engineer, and Cloud Data Architect, with strong demand across industries.
You will gain hands-on experience with Google Cloud Platform services including BigQuery, Cloud Dataflow, Cloud Dataproc, Cloud Pub/Sub, Cloud Storage, BigQuery ML, Data Catalog, and IAM. You will also use Python and SQL extensively for building and querying data pipelines.
The Micro Degree course is an online LIVE course, where LIVE sessions will be conducted online on our Classroom platform. Prior to the start of the course, you'll receive preparatory material in the form of recorded content which can be access on the same platform.
In this course instructors will use English language for teaching.
Upon successful registration, you will receive a confirmation email on your registered email ID. In this email you will receive login details for your newly created account on the Edyoda Classroom platform (https://classroom.edyoda.com). Additionally, you will receive a PDF guide containing step-by-step instructions on how to utilize the platform to access live sessions and learning materials.
Our instructors are the industry experts with a minimum working experience of 10 years with a strong technical and teaching background. They bring industry knowledge and practical expertise to the course.
Yes, the course includes online assignments, quizzes, and a final project to reinforce your learning and assess your proficiency in Google Cloud Professional Data Engineer Certification.
Yes, you can interact with instructors and fellow students through discussion forums, live Q&A sessions. We encourage a supportive learning community.
We offer a 100% money-back guarantee to ensure your complete satisfaction. If you're not satisfied, you can request a full refund within 3 days of purchase or before the second session, whichever comes earlier. Simply contact our support team(support@edyoda.com) with your purchase details, such as the order ID or email address, and share your reason for the refund. Requests made after 3 days or after the second session will not be eligible for a refund. There are no hidden charges, you will receive the full amount paid. Refunds are processed within 7–10 business days and credited back to your original payment method.
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