Build RAG Apps on Google Cloud Training for Cloud Engineers
Master Retrieval-Augmented Generation (RAG) on Google Cloud by building secure, scalable AI applications using Vertex AI (Gemini), Vertex AI Vector Search, Cloud Storage, BigQuery, and Cloud Run. This hands-on training helps you design document ingestion pipelines, implement embedding and retrieval workflows, and deploy enterprise-ready AI assistants that provide grounded responses from enterprise data.
+1,200 Enrolled
Course Description
Build RAG on Google Cloud Course Overview Overview
1000+
Students Enrolled
60 Hours
Course Duration
20 Labs
Hands-on Labs
1 End-to-End RAG Project
Capstone Projects
20 Modules
Modules Covered
what will you get
Key Features & Highlights
Vertex AI (Gemini) Implementation
Learn how to build Generative AI applications using Vertex AI (Gemini) for grounded responses, embeddings generation, and enterprise-ready AI workflows.
Vertex AI Vector Search
Implement semantic retrieval using Vertex AI Vector Search (Matching Engine) to index embeddings and retrieve relevant information from enterprise documents.
Enterprise Document Ingestion Pipelines
Design document ingestion pipelines using Cloud Storage and Document AI to extract, clean, and prepare enterprise data for RAG-based AI systems.
Secure Cloud AI Architecture
Understand IAM roles, service accounts, and governance practices required to build secure and compliant AI applications on Google Cloud.
Why do Build RAG Apps on Google Cloud Training for Cloud Engineers at Nevo Learn
Learn like never before. Not just learning, you interact and gain real experience.
- Get practical, real-world learning experience
- Engage in interactive sessions and activities
- Apply concepts through hands-on exercises
Build skills that matter. Go beyond theory and develop job-ready expertise.
- Track and measure your skill progress
- Identify strengths and areas for improvement
- Gain industry-relevant knowledge and tools
Achieve your career goals with structured learning and expert guidance.
- Learn from industry experts and mentors
- Prepare for certifications and real-world challenges
- Boost your career growth with in-demand skills
QUICK FACTS
Build RAG Apps on Google Cloud Training for Cloud Engineers Curriculum
Concepts
● What is cloud? What is Google Cloud Platform (GCP)?
● Projects, billing basics (high-level), regions/zones
● Console tour and service navigation
Lab 1
● Create/select a GCP project (or use a provided training project)
● Enable key APIs (guided)
● Set budgets/alerts (training-safe setup)
Concepts
● IAM users, roles, permissions (beginner explanation)
●
Service accounts and why they matter
for apps
Lab 2
●
Create a service account
●
Assign least-privilege roles for
Storage + Vertex AI
●
Test access with a simple console
check
Concepts
● Buckets, objects, folders (prefix), lifecycle basics
●
Organizing documents for AI
retrieval
Lab 3
●
Create a bucket and upload sample
PDFs
●
Set folder structure (by
department/type)
●
Apply basic access control (who can
read what)
Concepts
● What LLMs do (and why hallucinations happen)
●
What “grounding” means and why
enterprises need it
●
RAG overview: retrieve then generate
Lab 4
●
Use Vertex AI Studio to test prompts
●
Compare: ungrounded vs grounded
response behavior (demo dataset)
Concepts
● End-to-end RAG flow: ingest → chunk → embed → vector store → retrieve →
answer
●
Managed services approach vs
building everything yourself
Lab 5
●
Draw your RAG architecture diagram
(template)
●
Map each step to a GCP managed
service
QUICK FACTS
About Build RAG Apps on Google Cloud Training for Cloud Engineers Certification
Follow these simple steps to earn your professional certification and validate your expertise.
Enroll through official registration from Nevolearn
Complete 60 hours of instructor-led Google Cloud training
Participate in guided hands-on labs
Build and deploy a complete RAG assistant
Present architecture and evaluation results
QUICK FACTS
Prerequisites
- Basic computer literacy (files, browser usage, and email)
- No advanced coding skills required
- Basic understanding of cloud concepts is helpful but not mandatory
- Interest in AI application development and automation
QUICK FACTS
Who should attend the Build RAG Apps on Google Cloud Training for Cloud Engineers training
This course is designed for learners and professionals who want to build Generative AI applications on Google Cloud using Retrieval-Augmented Generation (RAG). It is suitable for freshers, engineering graduates, and beginners from technical or non-CS backgrounds who want to develop practical AI skills. Cloud beginners looking to gain experience with Google Cloud AI services such as Vertex AI, Vector Search, and Cloud Run can also benefit from this program. The training is also valuable for software developers, application developers, support engineers, QA professionals, and operations teams who want to understand how enterprise AI assistants are built and deployed. Business analysts and IT professionals interested in AI automation and knowledge retrieval systems can use this course to transition into Generative AI and cloud-based AI development roles.
COMMON QUESTIONS
Build RAG Apps on Google Cloud Training for Cloud Engineers FAQs
Yes. The course starts with cloud fundamentals and RAG basics explained in simple language. Even learners from non-CS backgrounds can follow the structured labs and progressively build their understanding.
No. The training focuses on Google managed services such as Vertex AI, Vector Search, and Cloud Run. Some basic scripting may be demonstrated, but heavy programming is not required.
You will work with Vertex AI (Gemini), Vertex AI Vector Search, Cloud Storage, BigQuery, Document AI, IAM, Secret Manager, Cloud Logging, and Cloud Run.
Yes. The capstone project requires you to build a complete working RAG assistant including ingestion, embeddings, retrieval, grounding, evaluation, and deployment.
A normal chatbot generates responses from general training data and may hallucinate. A RAG system retrieves relevant enterprise documents first and then generates grounded answers based on that retrieved content.
Yes. You will implement IAM-based access control, service accounts, document isolation strategies, and safe configuration practices aligned with enterprise governance standards.
Yes. You will create a structured test dataset, evaluate retrieval accuracy, score AI responses using a rubric, and iteratively improve your system.
Yes. The course explains token usage costs, vector search pricing factors, storage considerations, and architecture decisions that affect cloud spend.
Yes. The curriculum is designed around enterprise use cases such as HR assistants, IT knowledge bots, compliance search tools, and internal knowledge retrieval systems.
You will receive certification, a capstone project, architecture documentation, evaluation results, and a portfolio-ready RAG implementation suitable for interviews.
Skills Covered
What Will You Learn?
QUICK FACTS
Soaring Demand and Accelerated Growth
Google Cloud RAG Engineer
Annual Salary
Workers/SalaryHiring Companies
Build document ingestion pipelines for enterprise knowledge systems
FOR Google Cloud RAG Engineer
Annual Salary
Workers/SalaryHiring Companies
Build document ingestion pipelines for enterprise knowledge systems
for Google Cloud RAG Engineer
Still have a question? Get in Touch with our Experts
QUICK FACTS
Set your teams up with this course
This Google Cloud RAG training helps learners build practical expertise in developing enterprise-ready Generative AI applications using Google Cloud managed services. Participants gain hands-on experience designing document ingestion pipelines, generating embeddings, implementing vector search, and deploying scalable Retrieval-Augmented Generation (RAG) applications using Vertex AI, Cloud Storage, BigQuery, and Cloud Run.
By completing this course, learners will understand how to create grounded AI systems that retrieve accurate information from enterprise documents instead of generating unpredictable responses. The training also introduces best practices for security, IAM configuration, monitoring, evaluation, and cost optimization required for real-world AI deployments.
The program helps professionals strengthen their Google Cloud AI skills, build a portfolio-ready RAG assistant project, and improve career opportunities in Generative AI, cloud AI engineering, and enterprise AI solution development.
Transforming your team
QUICK FACTS
Meet the team that is invested in your success
Arjun Mehta
Artificial intelligence Instructor
Experience
1-3 Years
Experienced AI trainer specializing in Generative AI, Machine Learning, Deep Learning, prompt engineering, and practical AI solutions for business and...
Arjun Mehta
Artificial intelligence Instructor
Experience
1-3 Years
Experienced AI trainer specializing in Generative AI, Machine Learning, Deep Learning, prompt engineering, and practical AI solutions for business and...
CERTIFICATION
Earn a certificate on completion of this course
After finishing Nevolearn's Build RAG Apps on Google Cloud Training for Cloud Engineers course, you'll earn an industry-recognized professional certificate. This certificate is designed for sharing on LinkedIn, allowing you to highlight your accomplishments and share your new skills with your network.
Validating your expertise with a professional certification helps you stand out in the job market and provides tangible proof of your commitment to continuous learning and professional growth.
Still have a question? Get in Touch with our Experts
TESTIMONIALS
What Learners are Saying
QUICK FACTS
Recommended Courses
The most effective project-based immersive learning experience The most effective project-based immersive learning experience The most effective project-based immersive learning experience
Recommended Articles
The most effective project-based immersive learning experience The most effective project-based immersive learning experience The most effective project-based immersive learning experience
Best Ways to Prioritize User Stories
Learn the most effective techniques to prioritize user stories in Agile Scrum and manage your product backlog efficiently.
Read more
Project Management
Insights, guides, and resources on project management certifications, methodologies, Agile practices, and career growth for project management professionals.
Read moreStill have a question? Get in Touch with our Experts
This Google Cloud RAG training program teaches professionals how to build enterprise-ready Retrieval-Augmented Generation (RAG) applications using Google Cloud Platform. Learners gain hands-on experience with Vertex AI (Gemini), Vertex AI Vector Search, Cloud Storage, BigQuery, Document AI, and Cloud Run to design secure, scalable AI assistants. The course covers document ingestion pipelines, embedding generation, vector indexing, retrieval workflows, prompt grounding, and deployment strategies. By completing this training, participants can confidently develop production-grade Generative AI applications on Google Cloud aligned with modern enterprise architecture and governance standards.
Build RAG on Google Cloud Using Google Managed Services is a cloud-focused Google Cloud RAG training and RAG on Google Cloud course designed to help learners build secure, enterprise-ready Retrieval-Augmented Generation (RAG) applications using Google Cloud Platform. This Google Cloud Generative AI course and generative AI training on GCP focuses on implementing production-ready AI systems using Vertex AI (Gemini), Vertex AI Vector Search, Cloud Storage, BigQuery, Document AI, and Cloud Run.
As part of this Vertex AI RAG training, Gemini Vertex AI training, and Vertex AI Vector Search training, learners gain practical experience designing document ingestion pipelines, generating embeddings, and implementing retrieval workflows required to build RAG applications on GCP. The program also covers grounding model responses and RAG deployment on Cloud Run to create scalable AI assistants within secure GCP environments.
This enterprise RAG training helps professionals develop real-world skills in retrieval augmented generation Google Cloud, vector indexing, and semantic search, making it suitable for those pursuing Google Cloud AI engineer training, vector search GCP course expertise, or a GCP AI training certification / Google Cloud AI certification course aligned with modern enterprise AI implementations.