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Flagship ProgramHigh DemandGrowthIntermediate6 weeks
GCP Cloud Engineering
GCP Cloud Engineering is a 6-week course giving hands-on experience with Google Cloud Platform — compute, storage, BigQuery for data warehousing, deploying containerized apps on Kubernetes Engine (GKE), and IAM — building and deploying real applications specifically on GCP, for developers who want GCP-specific skills for cloud or data/AI roles.
Get hands-on with Google Cloud Platform — compute, storage, BigQuery, Kubernetes Engine, and IAM — building and deploying real applications on GCP specifically.
What you'll learn
Core GCP compute and storage services
BigQuery for data warehousing and analytics
Deploying containerized apps on GKE
IAM and cost management on GCP
Course details
Duration
6 weeks
Best for
Developers who want GCP-specific skills for cloud roles or GCP-based data/AI work
Enrollment isn't open for this course yet — check back soon or contact us.
Course Curriculum
A module-by-module breakdown of what you'll cover in GCP Cloud Engineering.
01Part 1: Data Engineering and Cloud Foundations
3 topicsWeek 1
- Data Engineering Roles and Lifecycle
- Data Architecture Fundamentals
- Reliability and Data Quality
02Part 2: Python SQL Linux and Git
3 topicsWeek 2
- Python for Data Pipelines
- SQL for Data Engineering
- Linux Git and Development Workflow
03Part 3: Google Cloud Platform Foundations
3 topicsWeek 2
- Resource Hierarchy Billing and Tools
- Identity Access and Secrets
- Networking Compute and Serverless
04Part 4: Cloud Storage and Data Ingestion
3 topicsWeek 3
- Cloud Storage
- Batch Ingestion and Transfer Services
- Event Driven Ingestion
05Part 5: BigQuery Data Warehouse
4 topicsWeek 3
- BigQuery Architecture and Loading
- Warehouse Modelling and SQL
- Performance Cost and Security
- BigQuery Operations and Analytics
06Part 6: Batch Processing with Dataflow and Dataproc
3 topicsWeek 4
- Apache Beam Fundamentals
- Dataflow Batch Pipelines
- Dataproc and Spark
07Part 7: Streaming Data Engineering
3 topicsWeek 4
- Pub Sub Fundamentals
- Beam Windowing and Triggers
- Dataflow Streaming Operations
08Part 8: Databases and Data Serving
3 topicsWeek 5
- Cloud SQL AlloyDB and Spanner
- Bigtable Firestore and Memorystore
- Serving and Data APIs
09Part 9: Transformation Orchestration and Integration
3 topicsWeek 5
- Cloud Composer and Airflow
- Dataform and SQL Transformation
- Integration Services
10Part 10: Governance Security and Data Quality
3 topicsWeek 6
- Dataplex Universal Catalog
- Security Privacy and Compliance
- Data Quality Observability and Governance
11Part 11: Infrastructure Automation Monitoring and Cost
3 topicsWeek 6
- Terraform and Infrastructure as Code
- CI CD and Release Engineering
- Monitoring Reliability and Cost Optimisation
12AI Pro
3 topicsWeek 7
- Using Claude, ChatGPT, and Perplexity for Google Cloud Infrastructure Work
- Verifying AI-Suggested GCP Configurations Before Applying Them
- Project: AI-Assisted GCP Configuration with Scope and Role Verification
Tools & Technologies
Hands-on practice with the same tools used by working professionals.
GooGoogle Cloud Platform
ComCompute Engine
CloCloud Storage
BigBigQuery
GKEGKE
CloCloud Functions
TFTerraform
ChaChatGPT
ClaClaude
PerPerplexity
Want to learn just one piece first?
GCP Cloud Engineering bundles all of these into one program — but each is also available as its own standalone course if you'd rather learn (or brush up on) a single skill first.
Need this built for your business instead?
If you'd rather have it done than learn it, our solutions team delivers this work for businesses directly.
Real-Time, Industry-Based Projects
This is project-based learning modeled on real industry scenarios — you'll build portfolio-ready work as you go, not just watch lectures.
Deployed web app on Compute Engine with a load balancer
BigQuery data warehouse with scheduled queries
Containerized microservice deployed to GKE
Serverless data pipeline using Cloud Functions and Cloud Storage triggers
Every course includes a guided internship on top of your project work — so you graduate with real experience, not just a certificate.
Communication & Soft Skills
Built into every course, alongside the technical curriculum.
Communication Skills
Practice explaining technical work clearly to teammates, managers, and clients.
Practical AI Skills
Hands-on training in using AI tools well — prompting, everyday workflows, and where AI actually helps versus where it doesn't.
Teamwork & Collaboration
Work in small project teams using real workflows like stand-ups and code reviews.
Problem Solving
Build the habit of breaking down ambiguous problems into clear, solvable steps.
Time Management
Learn to plan, prioritize, and deliver project work against realistic deadlines.
Presentation Skills
Present your project work and results with confidence, as you would to a client.
Resume & Profile Building
Build a strong resume, LinkedIn profile, and project portfolio that recruiters notice.
Interview Preparation
Mock interviews and portfolio reviews to get you ready for real job applications.
Career & Placement Support
100% of students enrolled in GCP Cloud Engineering get full access to placement support — real tools and guidance, not just a promise. This is support and access, not a guaranteed job outcome.
Resume Builder
A resume auto-built from your real completed projects and certificates, ready to export.
Shareable Portfolio
A public portfolio page showcasing your approved projects, with a link you can share with employers.
Interview Preparation
Guidance on presenting your projects and experience clearly in real interviews.
Peer & Mentor Community
Ongoing access to our learner community for questions, feedback, and support after you finish.
What Your Certificates Look Like
Real, verifiable certificates with your name, GCP Cloud Engineering, and a QR code anyone can scan to confirm they're genuine — one for completing the course, and a separate one if you take the internship track.
Course Completion Certificate
SAMPLE
Data24ZoneCertificate of Completion
Illustrative recipient
Your Name Here
Example certificate for completion of
GCP Cloud Engineering
- Certificate No.
- D24-SAMPLE
- Mode
- Self-Paced
- Duration
- 6 weeks
- Example issue date
- On completion
Sample only — not a real, issued certificate.
Verification is available only on issued certificates.
Internship Completion Certificate
SAMPLE
Data24ZoneCertificate of Internship
Illustrative recipient
Your Name Here
Example certificate for completion of
GCP Cloud Engineering
- Certificate No.
- D24-SAMPLE
- Mode
- Internship
- Duration
- 6 weeks
- Example issue date
- On completion
Sample only — not a real, issued certificate.
Verification is available only on issued certificates.
Frequently Asked Questions
What does a GCP data engineer do?
A GCP data engineer builds data pipelines and warehouses on Google Cloud — ingesting data into Cloud Storage and Pub/Sub, processing it with Dataflow or Dataproc, modelling it in BigQuery, and orchestrating and securing the whole platform.
What is BigQuery used for?
BigQuery is Google Cloud's serverless data warehouse, used to store and run fast SQL analytics over very large datasets without managing servers. The program has a dedicated part on BigQuery architecture, modelling, performance, and cost.
Do I need cloud experience before learning GCP data engineering?
No prior GCP experience is needed, but basic Python and SQL help. The program covers Python, SQL, Linux, and Git in an early part before Google Cloud foundations.
What will I learn in the GCP Cloud Engineering course?
You'll learn: Core GCP compute and storage services; BigQuery for data warehousing and analytics; Deploying containerized apps on GKE; IAM and cost management on GCP.
What tools and technologies does the GCP Cloud Engineering course cover?
This course covers: Google Cloud Platform, Compute Engine, Cloud Storage, BigQuery, GKE, Cloud Functions, Terraform, ChatGPT, Claude, Perplexity.
Is the GCP Cloud Engineering course beginner-friendly?
This is a intermediate-level course, so it assumes some prior familiarity with the subject.
How long does the GCP Cloud Engineering course take to complete?
The course is designed to be completed in approximately 6 weeks, depending on your pace.
What enrollment options are available for GCP Cloud Engineering?
Live Class (₹12,999) — Instructor-led live cohort with doubt-clearing sessions — includes both the course and internship certificates. Recorded Batch (₹7,999) — Full recordings of a completed live batch — includes both the course and internship certificates. Internship (₹2,499) — Work through real projects with our team and earn an internship certificate (course certificate not included). Self-Paced (₹4,999) — Learn anytime with the full recorded curriculum and community access.
Is there an internship option for GCP Cloud Engineering?
Yes — enrolling in the Internship track (or the Live/Recorded tracks, which include it) means working through real projects with our team and earning a separate Internship Certificate, in addition to the course completion certificate for Live/Recorded enrollments.
Will I get a certificate after completing GCP Cloud Engineering?
Yes. Self-paced enrollment earns a course completion certificate once your final project is reviewed and approved. Internship enrollment earns an internship certificate once your internship projects are approved. Live and Recorded enrollments earn both. Every certificate is publicly verifiable on our website and can be added directly to your LinkedIn profile.
What kind of projects will I build in GCP Cloud Engineering?
You'll work on real projects such as: Deployed web app on Compute Engine with a load balancer; BigQuery data warehouse with scheduled queries; Containerized microservice deployed to GKE; Serverless data pipeline using Cloud Functions and Cloud Storage triggers.
Is placement support included with GCP Cloud Engineering?
Yes — every enrolled student gets full access to our placement support: resume building, a shareable project portfolio, mock interview preparation, and guidance applying what you've built to real job applications. This is support and access, not a guaranteed job outcome — how quickly it leads to an offer depends on the market and your own effort.
