Google Cloud Certified Professional Data Engineer

Google Cloud Certified Professional Data Engineer is a highly valued certification from Google that validates professionals’ design, build and operate powerful big data and machine learning solutions using Google Cloud Platform. This Google Cloud Certified Professional Data Engineer course in Dubai is designed to enable professionals to solidify their foundations in Data Engineering and Machine Learning field. This comprehensive Google Cloud Certified Professional Data Engineer training prepares professionals for the certification exam and helps them take their careers to the next level.

Accredited By

  • 5 weeks | 40 hours Bootcamp
  • Online / Offline / Blended
  • 14 Jul, 2022 / 10 Aug, 2022
  • Additional Program Dates
  • 100K+ Happy Students

(400+ Google Reviews)

Enquire Now

What is this Google Cloud Certified Professional Data Engineer course all about?

The Google Cloud Certified Professional Data Engineer course in Dubai provides professionals with a practical understanding of ways to design, build, maintain, and troubleshoot data processing systems. The GCP Data Engineer course familiarizes participants with the crucial aspects of the system including reliability, scalability, fault-tolerance, fidelity, security, and efficiency. This comprehensive Google Cloud Certified Professional Data Engineer course incorporates ample hands-on lab sessions that help participants gain practical hands-on experience with the concepts explained throughout the modules.

What is this Google Cloud Certified Professional Data Engineer course all about?

The Google Cloud Certified Professional Data Engineer course in Dubai provides professionals with a practical understanding of ways to design, build, maintain, and troubleshoot data processing systems. The GCP Data ...

Read More

Why is getting trained as Google Cloud Certified Professional Data Engineer important?

Gaining a working knowledge of relevant GCP data processing tools and technologies can bring endless opportunities to professionals. This Google Cloud Certified Professional Data Engineer training in Dubai explains core concepts of data engineering using the Google cloud platform. Furthermore, this GCP Data Engineer training is a full-fledged training program that increases professionals' proficiency and competency and imparts critical job skills for Data Engineer roles.

Why is getting trained as Google Cloud Certified Professional Data Engineer important?

Gaining a working knowledge of relevant GCP data processing tools and technologies can bring endless opportunities to professionals. This Google Cloud Certified Professional Data Engineer training in Dubai exp...

Read More

Why do companies hire professionals with Google Cloud Certified Professional Data Engineer certification?

Google Cloud Certified Professional Data Engineer is a globally valued certification that validates one’s proficiency in Data Engineering and Machine Learning.  In today’s data-driven world, organizations are on the run for skilled and certified data engineering professionals. They hire Google Cloud Certified Professional Data Engineer for their expert knowledge of data processing systems. Their ability to implement data processing and machine learning solutions on the Google Cloud Platform (GCP) makes them of great value to organizations.

Why do companies hire professionals with Google Cloud Certified Professional Data Engineer certification?

Google Cloud Certified Professional Data Engineer is a globally valued certification that validates one’s proficiency in Data Engineering and Machine Learning.  In today’s d...

Read More

Industry Trends

Today, big data is among the handful of industries that saw growth and is expected to expand significantly in the coming years. The Google Cloud Certified Professional Data Engineer certification comes with its own set of merits and opportunities in the market. Let us see how.

Market trends Market trends

The Google Cloud Certified Professional Data Engineer is one of the most sought-after credentials among big data and analytics professionals. Owing to their popularity in the global job market, top companies such as PayPal, Target, Twitter, and many more constantly hire professional GCP data engineers. The job prospects for Certified Data Engineers are positive as ​​data engineering is currently one of tech’s fastest-growing sectors.

Salary Trend Salary Trends

As the Big Data market continues to grow in both volume and complexity, the demand for certified Data Engineers is growing rapidly. Certified Data Engineers have higher chances of better remuneration as Google Cloud Data Engineer certification stands third among the top-paying certifications worldwide. According to the data from Glassdoor.com, the average salary for a Data Engineer is AED 23,500 per month in Dubai, United Arab Emirates.

Demand & Opportunities

With the integration of AI and ML with data technologies, the demand for Certified Data Engineers is skyrocketing. The Google Cloud Certified Professional Data Engineer certification gives an assurance of the necessary competency in related roles, thus making these opportunities easier to avail.

A few of the most-sought data engineering jobs available in the Dubai region (as observed in popular Dubai job portals) follow:

  1. Data Engineers create and manage data services, design and build data extraction, transformation, and load processes through custom data pipelines
  2. Machine Learning Engineers create programs and algorithms that enable machines to take actions without being directed
  3. AI Engineers build AI models using machine learning algorithms and deep learning neural networks to draw business insights
  4. Data Scientists combine computer science, modeling, statistics, analytics, and math skills to help organizations to solve vexing problems
  5. Data Architect analyzes the data needs of the company and uses skills in coding to maintain secure databases

Course Outcome

Successful completion of the Google Cloud Certified Professional Data Engineer certification course will help you to:

  • Explore core concepts of data engineering using the Google cloud platform
  • Master Google cloud platform services and solidify your foundation in Data Engineering and Machine Learning field
  • Learn how to ​​design, build and operationalize data solutions
  • Build and operationalize data processing systems
  • Master techniques to utilize the cloud efficiently to store and retrieve data

Course Module

Selecting the appropriate storage technologies

  • Mapping storage systems to business requirements
  • Data modeling
  • Trade-offs involving latency, throughput, transactions
  • Distributed systems
  • Schema design

Designing data pipelines

  • Data publishing and visualization 
  • Batch and streaming data 
  • Online (interactive) vs. batch predictions
  • Job automation and orchestration

Designing a data processing solution

  • Choice of infrastructure
  • System availability and fault tolerance
  • Use of distributed systems
  • Capacity planning
  • Hybrid cloud and edge computing
  • Architecture options 

Migrating data warehousing and data processing

  • Awareness of current state and how to migrate a design to a future state
  • Migrating from on-premises to cloud (Data Transfer Service, Transfer Appliance, Cloud Networking)
  • Validating a migration

Leveraging pre-built ML models as a service

  • ML APIs 
  • Customizing ML APIs 
  • Conversational experiences 

Deploying an ML pipeline

  • Ingesting appropriate data
  • Retraining of machine learning models (AI Platform Prediction and Training, BigQuery ML, Kubeflow, Spark ML)
  • Continuous evaluation

Choosing the appropriate training and serving infrastructure

  • Distributed vs. single machine
  • Use of edge compute
  • Hardware accelerators 

Measuring, monitoring, and troubleshooting machine learning models

  • Machine learning terminology 
  • Impact of dependencies of machine learning models
  • Common sources of error

Building and operationalizing storage systems

  • Effective use of managed services (Cloud Bigtable, Cloud Spanner, Cloud SQL, BigQuery, Cloud Storage, Datastore, Memorystore)
  • Storage costs and performance
  • Life cycle management of data

Building and operationalizing pipelines

  • Data cleansing
  • Batch and streaming
  • Transformation
  • Data acquisition and import
  • Integrating with new data sources

Building and operationalizing processing infrastructure

  • Provisioning resources
  • Monitoring pipelines
  • Adjusting pipelines
  • Testing and quality control

Designing for security and compliance

  • Identity and access management 
  • Data security (encryption, key management)
  • Ensuring privacy 
  • Legal compliance 

Ensuring scalability and efficiency

  • Building and running test suites
  • Pipeline monitoring 
  • Assessing, troubleshooting, and improving data representations and data processing infrastructure
  • Resizing and autoscaling resources

Ensuring reliability and fidelity

  • Performing data preparation and quality control 
  • Verification and monitoring
  • Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
  • Choosing between ACID, idempotent, eventually consistent requirements

Ensuring flexibility and portability

  • Mapping to current and future business requirements
  • Designing for data and application portability 
  • Data staging, cataloging, and discovery

Course Module

Selecting the appropriate storage technologies

  • Mapping storage systems to business requirements
  • Data modeling
  • Trade-offs involving latency, throughput, transactions
  • Distributed systems
  • Schema design

Designing data pipelines

  • Data publishing and visualization 
  • Batch and streaming data 
  • Online (interactive) vs. batch predictions
  • Job automation and orchestration

Designing a data processing solution

  • Choice of infrastructure
  • System availability and fault tolerance
  • Use of distributed systems
  • Capacity planning
  • Hybrid cloud and edge computing
  • Architecture options 

Migrating data warehousing and data processing

  • Awareness of current state and how to migrate a design to a future state
  • Migrating from on-premises to cloud (Data Transfer Service, Transfer Appliance, Cloud Networking)
  • Validating a migration

Building and operationalizing storage systems

  • Effective use of managed services (Cloud Bigtable, Cloud Spanner, Cloud SQL, BigQuery, Cloud Storage, Datastore, Memorystore)
  • Storage costs and performance
  • Life cycle management of data

Building and operationalizing pipelines

  • Data cleansing
  • Batch and streaming
  • Transformation
  • Data acquisition and import
  • Integrating with new data sources

Building and operationalizing processing infrastructure

  • Provisioning resources
  • Monitoring pipelines
  • Adjusting pipelines
  • Testing and quality control

Leveraging pre-built ML models as a service

  • ML APIs 
  • Customizing ML APIs 
  • Conversational experiences 

Deploying an ML pipeline

  • Ingesting appropriate data
  • Retraining of machine learning models (AI Platform Prediction and Training, BigQuery ML, Kubeflow, Spark ML)
  • Continuous evaluation

Choosing the appropriate training and serving infrastructure

  • Distributed vs. single machine
  • Use of edge compute
  • Hardware accelerators 

Measuring, monitoring, and troubleshooting machine learning models

  • Machine learning terminology 
  • Impact of dependencies of machine learning models
  • Common sources of error

Designing for security and compliance

  • Identity and access management 
  • Data security (encryption, key management)
  • Ensuring privacy 
  • Legal compliance 

Ensuring scalability and efficiency

  • Building and running test suites
  • Pipeline monitoring 
  • Assessing, troubleshooting, and improving data representations and data processing infrastructure
  • Resizing and autoscaling resources

Ensuring reliability and fidelity

  • Performing data preparation and quality control 
  • Verification and monitoring
  • Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
  • Choosing between ACID, idempotent, eventually consistent requirements

Ensuring flexibility and portability

  • Mapping to current and future business requirements
  • Designing for data and application portability 
  • Data staging, cataloging, and discovery

Program Dates

14 Jul
  • 09:00 AM
  • Thu
  • Classroom
Enquire Now
24 Jul
  • 07:00 PM
  • Sun
  • Online Live
Enquire Now
31 Jul
  • 11:00 AM
  • Sun
  • Classroom
Enquire Now
10 Aug
  • 11:00 AM
  • Wed
  • Classroom
Enquire Now

Expert Instructors & Teaching Methods

Our Trainer got 15 years of rich & extensive experience in Sr. IT Infrastructure Solution Architect / Big Data Consultant / IoT Solution Architect [On Premises Data Center Solution / Private Cloud / Public Cloud / Hybrid Cloud /Community Cloud] on various Cloud Provider Vendors i.e. Amazon, Microsoft, VMware etc. Amazon Certified and Microsoft Certified expert. Having Highest Level of Multi-Vendor technologies Certifications in Cloud Solution Architect: - Amazon, Microsoft, VMware, EMC & Cloud School-Canada. Also have Highest Level certification in Data Center Build & Design solution i.e. CDCP [Certified Data Center Professional] & CDCS [Certified Data Center Specialist]. Currently Associated with Dubai Government as Senior IT Infrastructure Solution Architect. Also Working as a Freelancer / Corporate Trainer of Various Amazon & Microsoft Level certification courses Certifications: - Microsoft Azure Dev-ops Engineer, Amazon Solution Architect Associate, Professional, Sysops Associate, MCSE-Server Infrastructure, Messaging-Exchange Server, Communication-Lync Server, Office 365 & Azure Solution. Delivered 25 Major IT Projects in Infrastructure Solutions of Top Most UAE Private & Government Sectors in Dubai & Abu Dhabi. Completed 20 IT Infrastructure Projects of MNC Company Overseas Location India, USA, UK, Canada, France, Germany, Brazil, Malaysia, Australia, China, Vietnam, Thailand, Singapore. Worked on Five Enterprise Level Data Center Projects based on Cisco V-Block Solution (Cisco UCS Servers, EMC Storage & VMware Virtualization Environment)o Done approximately 10 Enterprise Level Data Center Projects in Microsoft Hyper-V & VMware Virtual Environment. Have B. Tech [Computer Science Engineering] degree along with Latest Professional certifications in Amazon, Microsoft, VMware & other IT Infrastructure Management solution. Got Charter Member Certificate from Microsoft on Exchange & Windows Server infrastructure Solution.

Trainer

Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

KHDA Certificate

Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

Why Count on Learners Point?

Being the leading provider of Google Cloud certification courses in Dubai, at Learners Point we help professionals master the necessary skill sets to successfully complete the Google Cloud Certified Professional Data Engineer certification.

Following are the USPs our Google Cloud Certified Professional Data Engineer certification course offers you:

  • We look at real-world scenarios organizations face and formulate our GCP Data Engineer training course evaluating practical requirements
  • Apart from theoretical knowledge, we also focus on practical case studies to give you a reality check and insight into what exactly will be asked of you while delivering in a demanding role
  • Our bespoke GCP Certified Data Engineer course also equips you with hands-on experience by offering assignments related to the actual work environment
  • Apart from organizing group sessions, we also offer a guided learning experience to enhance the quality of our GCP Data Engineer training program
  • We also take a discrete approach to career guidance so that one can be successfully placed as a professional

Learners Experience

"Eugene is an excellent teacher. He is efficient and makes a difficult subject simple. I'm very grateful for his teaching and patience in understanding the curriculum."

"Eugene is an excellent teacher. He is efficient and makes a difficult subject simple. I'm very grateful for his teachin [...]

Ami

student

"The instructor was very knowledgeable and used many real world examples. He did not read straight from the book. Added his own personality and perspectives."

"The instructor was very knowledgeable and used many real world examples. He did not read straight from the book. Added [...]

Gina M

IT Professional

Our Graduates

Our graduates are from big companies, small, companies, they are founders, career changers and life long learners. Join us and meet your tribe!

Frequently Asked Questions

With Big Data and Data Science taking over today’s business world, it is always a great choice to flourish in this domain. This sector offers ample job opportunities for professionals with the right skillset. With nearly every industry at its peak of major digital transformation, professionals can have a promising future with a career in Data Engineering.
The Google Cloud Certified Professional Data Engineer is one of the most sought-after credentials among big data and analytics professionals. Issued by Google, this GCP Data Engineer credential is valid for 2 years from the date of certification and is widely recognized by top-notch organizations. Owing to its value in the global business world, this certification can bring certified professionals a plethora of job opportunities and increased earning potential.
The Google Cloud Certified Professional Data Engineer training in Dubai is a perfect fit for any professional interested in enhancing their competency in Data Engineering and the ML field or wanting to prepare for the Google Cloud Certified Professional Data Engineer certification exam.
The training sessions at Learners Point are interactive, immersive, and intensive hands-on programs. We offer 3 modes of delivery and participants can choose from instructor-led classroom-based group coaching, one-to-one training session, or high-quality live and interactive online sessions as per convenience.
With technological advancements in the UAE, Dubai is now becoming the home to tech savvies. Professionals with significant experience in Data Engineering and conceptual understanding of AL and ML can bring their careers one level up. The demand for Data Engineering skilled professionals is all set to rise at an impressive rate in the UAE making it the ideal location for a futuristic career.
The potential for Big Data and Cloud technology is huge in the future as it is an unavoidable trend in a wide range of industries. Due to its complexity, professionals are to be trained by industry experts to master this field. This Google Cloud Certified Professional Data Engineer training in Dubai explains core concepts of data engineering using the Google cloud platform. Furthermore, this GCP Data Engineer training is a full-fledged training program that increases your proficiency and competency and imparts critical job skills for Data Engineer roles.
There are no specific prerequisites for enrolling in this Google Cloud Certified Professional Data Engineer course. However, we do recommend participants have a basic understanding of the cloud, databases, and data analysis.
In order to appear for the Google Cloud Certified Professional Data Engineer certification exam, candidates are to have 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud.
At Learners Point, if a participant doesn’t wish to proceed with the training after the registration due to any reason, he or she is entitled to a 100% refund. However, the refund will be issued only if we are notified in writing within 2 days from the date of registration. The refund will be processed within 4 weeks from the day of exit.

Frequently Asked Questions

With Big Data and Data Science taking over today’s business world, it is always a great choice to flourish in this domain. This sector offers ample job opportunities for professionals with the right skillset. With nearly every industry at its peak of major digital transformation, professionals can have a promising future with a career in Data Engineering.
With technological advancements in the UAE, Dubai is now becoming the home to tech savvies. Professionals with significant experience in Data Engineering and conceptual understanding of AL and ML can bring their careers one level up. The demand for Data Engineering skilled professionals is all set to rise at an impressive rate in the UAE making it the ideal location for a futuristic career.
The Google Cloud Certified Professional Data Engineer is one of the most sought-after credentials among big data and analytics professionals. Issued by Google, this GCP Data Engineer credential is valid for 2 years from the date of certification and is widely recognized by top-notch organizations. Owing to its value in the global business world, this certification can bring certified professionals a plethora of job opportunities and increased earning potential.
The potential for Big Data and Cloud technology is huge in the future as it is an unavoidable trend in a wide range of industries. Due to its complexity, professionals are to be trained by industry experts to master this field. This Google Cloud Certified Professional Data Engineer training in Dubai explains core concepts of data engineering using the Google cloud platform. Furthermore, this GCP Data Engineer training is a full-fledged training program that increases your proficiency and competency and imparts critical job skills for Data Engineer roles.
The Google Cloud Certified Professional Data Engineer training in Dubai is a perfect fit for any professional interested in enhancing their competency in Data Engineering and the ML field or wanting to prepare for the Google Cloud Certified Professional Data Engineer certification exam.
There are no specific prerequisites for enrolling in this Google Cloud Certified Professional Data Engineer course. However, we do recommend participants have a basic understanding of the cloud, databases, and data analysis.
In order to appear for the Google Cloud Certified Professional Data Engineer certification exam, candidates are to have 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud.
The training sessions at Learners Point are interactive, immersive, and intensive hands-on programs. We offer 3 modes of delivery and participants can choose from instructor-led classroom-based group coaching, one-to-one training session, or high-quality live and interactive online sessions as per convenience.
At Learners Point, if a participant doesn’t wish to proceed with the training after the registration due to any reason, he or she is entitled to a 100% refund. However, the refund will be issued only if we are notified in writing within 2 days from the date of registration. The refund will be processed within 4 weeks from the day of exit.
Call Now Enquire Now