Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
14 Hour(s) 5 Minute(s)
Language
English
Taught by
Cloud & AI Analytics
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
Master GCP Data Engineering with 100+ Hands-on Labs covering Key Modules for All Big Data Professionals.
[UPDATED - 2025] ONLY COURSE YOU NEED TO GET READY for Google Cloud (GCP) Certified Professional Cloud Data Engineer Exam!
Immerse in a classroom style coaching of GCP cloud data engineering certification topics. This course has 26+ Hours of insanely great video contents with 100+ hands-on Lab (Most Practical Course)
Cloud is the future and GCP is Fastest growing Public cloud. 87 percentage of Google Cloud certified individuals are more confident about their cloud skills.
Google Cloud Platform is one of the fastest-growing cloud service platforms offered today that lets you run your applications and data workflows at a 'Google-sized' scale.
Google Cloud Certified Professional Cloud Data Engineer certification is one of the most highly desired IT certifications out today. It is also one of the most challenging exams offered by any cloud vendor today. Passing this exam will take many hours of study, hands-on experience, and an understanding of a very wide range of GCP services.
Have a look at course curriculum, to see depth of Course coverage. Boost your confidence and career with this highly sought-after certification.
This course also comes with:
Lifetime access to all course material & updates
Q&A Section
Udemy Certificate of Completion
Don't wait another moment—your journey starts here! Enroll NOW, and I can't wait to welcome you inside the course! Let's embark on this exciting learning journey together.
Best Wishes,
Vignesh Sekar.
Course Content
- 39 section(s)
- 361 lecture(s)
- Section 1 Course Introduction
- Section 2 Overview On Cloud
- Section 3 Overview on Google Cloud Fundamentals
- Section 4 Getting Started With Google Cloud Platform - Cloud Service Models
- Section 5 Overview on Data Engineering
- Section 6 Storage Services in Google Cloud
- Section 7 Google Cloud Storage
- Section 8 Overview on Encryption options in Google Cloud
- Section 9 Database Service in Google Cloud
- Section 10 SQL databases - Quick guide
- Section 11 Google Cloud SQL
- Section 12 Google Cloud Spanner
- Section 13 NoSQL databases - Quick guide
- Section 14 Google Cloud BigTable
- Section 15 Google Cloud Datastore and Firestore
- Section 16 Google Cloud MemoryStore
- Section 17 Data Warehouse - Quick guide
- Section 18 Google Cloud BigQuery
- Section 19 Apache Kafka - Quick guide
- Section 20 Google Cloud PubSub
- Section 21 Big Data Tech Stacks- Quick guide
- Section 22 Google Cloud Data Fusion
- Section 23 Google Cloud Dataproc
- Section 24 Apache Beam - Quick guide
- Section 25 Google Cloud Dataflow
- Section 26 Google Cloud BigLake
- Section 27 Apache Airflow - Quick guide
- Section 28 Google Cloud Composer
- Section 29 Workflows - Cloud Integration Services
- Section 30 Google Cloud Data Catalog(Dataplex - Data governance)
- Section 31 Google Cloud Dataprep
- Section 32 Google Cloud Data Loss Prevention
- Section 33 Google Cloud Looker Studio
- Section 34 Google Cloud Datastream
- Section 35 Transfer Services in Google Cloud Platform
- Section 36 Overview on Google Cloud AI/ML Services
- Section 37 Case Study - Real Time Usecases
- Section 38 Professional Data Engineer - Preparing for Exam + Practice Exam
- Section 39 Congratulations - Course Completion
What You’ll Learn
- Start your journey on Google Cloud to become a Cloud Certified Professional Data Engineer
- Knowledge on all the essential concepts related to data engineers like Database(SQL & NoSQL), BigData, Apache Beam, Apache Airflow and Apache Spark.
- Brief Hands-on on GCP Core services like Compute engine, Kubernetes engine, App engine, Cloud Run and Cloud Functions.
- Understand the best practices for building available, scalable, resilient and secure data pipelines on the Google Cloud Platform
- You will acquire professional level data engineering skills in GCP like Cloud SQL, Cloud DataStore/Firestore, BigQuery, Memorystore and Cloud Storage.
- You will acquire professional level data engineering skills in google cloud like Cloud PubSub, Cloud Dataproc, Cloud Dataflow,DataFusion, BigTable and Composer.
- Hands on Practical Lab Sessions in Services like Cloud Data Prep, Data Catalog and Looker Studio
- Learn how to create big data ETL/ELT pipelines using Google Cloud platform
- You will learn how to monitor pipelines using Cloud Monitor, Cloud Logging and Error Reporting with a real-world project.
- Data-sets, Script files and command file used in lectures are available in resources tab. This will save your typing efforts.
- Implement real life end-to-end solutions by combining latest available services in Google Cloud Platform.
- Hands on Practical Lab Sessions
- Ideal for candidates aspiring to clear Professional Data Engineer exam
Skills covered in this course
Reviews
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SShiva
only ppt's
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SSundar
This course helped me a lot to overall understanding of GCP basics and good amount of knowledge on all the Analytics services in GCP. Not only this, I passed my Professional Data Engineer Certifcation exam on the first attempt after taking this course.
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DDivya
Excellent course, would recommend to anyone wanting to learn more about GCP Big Data Tech. Especially if you want to pass the GCP Data Engineering Certification. I think all of the content is very high-quality, and you will learn a lot!
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VVijay Sekar
I passed the GCP Data Engineer certification. This course has everything whatever you needed to pass this exam. All the services are covered in this course. One recommendation is that author should include a review lesson at the end of each section to summarize the key content. This will give students a quick and easy way to revisit and reinforce the essential knowledge from the chapter whenever they need a refresher. Everything is good.
