Earn Google Cloud Professional Data Engineer Certification
Design, Build, and Optimize Scalable Data Solutions on GCP.
March 1 @ 9:00 am – March 4 @ 5:00 pm UTC+5:30
About the event
This New year, are you ready to take your data engineering skills to the next level? Join us for an exclusive preparation course for the Google Cloud Professional Data Engineer Certification, to help you boost your career progression in the year 2025. This course is meticulously designed to provide participants with the skills and knowledge to design, build, secure, scale, and optimize data processing systems on the Google Cloud Platform (GCP) that powers the world.
Why Attend?
- Comprehensive Curriculum: Learn key concepts like data pipeline design, data modeling, and solution scalability.
- Hands-On Learning: Gain practical insights into GCP services like BigQuery, Dataflow, and Cloud Storage.
- Expert Guidance: Prepare with industry professionals and get ready for the certification exam with confidence.
Key Topics Covered:
- Data pipeline design and data modeling
- Operationalizing scalable solutions
- Ensuring security and reliability in data systems
- Insights into BigQuery, Dataflow, and Cloud Storage
Who Should Attend?
- Data Engineers: To manage and scale data pipelines
- Developers: Who work on Cloud, App, and Software
- Data Analysts: For creating and distributing data products
- Solution Architects: To design optimized solutions for tomorrow
- IT Professionals: For developing scalable, secure solutions
Prerequisites:
- Familiarity with cloud concepts and GCP basics
- Proficiency in SQL and Python/Java
- Basic understanding of data storage and data warehousing concepts
Note: Hands-on experience with GCP services is helpful but not mandatory.
Spots are limited! Secure your seat today.
Don’t miss this opportunity to elevate your career and become a certified Google Cloud Professional Data Engineer in 2025!
- Overview of Google Cloud Professional Data Engineer certification
- Exam format, objectives, and preparation tips
- Understanding the exam blueprint
- Introduction to GCP services and tools
- Navigating the GCP Console
- Understanding IAM and security basics
- Architecting batch and stream data pipelines
- Designing for scalability, reliability, and high performance
- Choosing the right GCP services for data processing (Dataflow, Dataproc)
- Exploring Cloud Storage, BigQuery, and Cloud SQL
- Optimizing data storage for cost and performance
- Implementing data partitioning and clustering
- Building ETL pipelines using Dataflow
- Introduction to Apache Beam
- Automating workflows with Cloud Composer
- Principles of data modeling for relational and NoSQL databases
- Best practices for designing schemas in BigQuery
- Performance tuning for query optimization
- Introduction to AI and ML services on GCP
- Using AI Platform and Vertex AI for model training and deployment
- Integrating ML into data pipelines
- Monitoring solutions with Stackdriver
- Debugging and troubleshooting pipeline issues
- Setting up alerts and automated responses
- Securing data at rest and in transit
- Implementing access control with IAM
- Compliance considerations (GDPR, HIPAA, etc.)
- Review of exam topics and key focus areas
- Practice questions and mock exams
- Time management strategies during the exam
- Tips for success from certified professionals