Conquer Google Cloud Data Engineering: Master the Professional Exam

Become a Google Cloud Professional Data Engineer and unlock exciting career opportunities!

Companies are ramping up the search for cloud experts who can take vast amounts of data and put it to work solving top business challenges, including customer satisfaction, production quality, and operational efficiency.

By earning the Google Cloud Professional Data Engineer Certification, you can demonstrate your skills and distinguish yourself among your peers with your ability to design data solutions that ensure maximum flexibility and scalability, meet security and compliance requirements, and enable data-driven decision making.

This comprehensive Udemy course equips you with the skills and knowledge to excel in the in-demand field of Google Cloud data engineering. Whether you’re a data enthusiast, an IT professional, or aspiring for a data engineering role, this course provides a solid foundation to launch your career.

What you’ll learn:

• Master core GCDP services: Gain in-depth knowledge of Cloud Storage, BigQuery, Dataflow, Cloud Functions, Pub/Sub, and Cloud SQL for data storage, processing, analysis, and machine learning.
• Build robust data pipelines: Design and implement data pipelines for both batch and streaming data processing using Dataflow.
• Ace the Professional Exam: Prepare to confidently take and pass the Google Cloud Professional Data Engineer exam with comprehensive coverage of all exam objectives.

A Professional Data Engineer makes data usable and valuable for others by collecting, transforming, and publishing data. This individual evaluates and selects products and services to meet business and regulatory requirements. A Professional Data Engineer creates and manages robust data processing systems. This includes the ability to design, build, deploy, monitor, maintain, and secure data processing workloads.

By the end of this course, you’ll be well-equipped to:

• Design and implement data pipelines for various use cases.
• Manage and analyze data using powerful Google Cloud services.
• Confidently navigate the Google Cloud Professional Data Engineer exam.
• Apply your skills to solve real-world data engineering challenges.
• Launch a successful career in the thriving field of Google Cloud data engineering.

Information about the exam

Here are details about the Professional Data Engineer Certification exam format, delivery options, renewal requirements, and more:

• Length: 2 hours
• Registration fee: $200 (plus tax where applicable)
• Languages: English, Japanese
• Format: 50-60 multiple choice and multiple select questions
• Exam delivery methods: a) Take the online-proctored exam from a remote location or b) Take the onsite-proctored exam at a testing center
• Certification Renewal / Recertification: Candidates must recertify in order to maintain their certification status. Your Professional Google Cloud certification is valid for two years from the date of certification (Foundational and Associate certifications are valid for three years after you pass). Recertification is accomplished by retaking the exam during the recertification eligibility time period and achieving a passing score. You may attempt recertification starting 60 days prior to your certification expiration date.

Enroll today and unlock your potential as a Google Cloud Professional Data Engineer!

Who this course is for:

• Data Engineers: Data professionals already working in the field who want to enhance their credentials and demonstrate proficiency in GCP-specific data engineering concepts will find this course valuable. It provides an opportunity to assess your knowledge, identify areas for improvement, and fine-tune your skills before sitting for the exam.
• IT Professionals Transitioning to Data Engineering: Professionals with a background in IT or related fields who are transitioning into data engineering roles and want to validate their GCP knowledge and skills will benefit from this course. It offers a targeted approach to prepare for the certification exam and bridge the gap between IT and data engineering domains.