+1,200 Enrolled
60 Hours Total Training Hours
20 Modules Total Modules
20+ Labs Hands-On Labs
1 End-to-End RAG Project Capstone Projects
8+ Services Cloud Tools Covered
800+ Professionals Students Enrolled
This course is designed to provide measurable, hands-on learning outcomes through structured modules and real-world labs. With extensive practical exposure to Google Cloud services, learners build and deploy a complete RAG application, gaining the skills required for enterprise-level AI development and cloud engineering roles.
We are currently preparing new batches for this course. Please check back later or contact us for more information.
Course Description
what will you get
Learn to build and deploy AI applications using Vertex AI (Gemini) with guided hands-on labs.
Build complete Retrieval-Augmented Generation pipelines from data ingestion to response generation.
Implement semantic search using embeddings and Vertex AI Vector Search for accurate retrieval.
Combine structured enterprise data with AI responses using BigQuery integration.
This course delivers a complete, hands-on learning experience focused on building production-ready RAG (Retrieval-Augmented Generation) applications on Google Cloud. It combines foundational concepts with real-world implementation using Vertex AI, Vector Search, BigQuery, and Cloud Run. Learners gain practical exposure to designing end-to-end AI pipelines, implementing secure cloud architectures, and deploying scalable AI applications aligned with enterprise standards. Through guided labs, real-world scenarios, and a capstone project, the course ensures strong technical understanding and job-ready skills in Generative AI and cloud engineering.
Follow these simple steps to earn your professional certification and validate your expertise.
This course is ideal for beginners and professionals who want to build expertise in Generative AI and cloud-based application development. It is suitable for freshers, developers, cloud engineers, analysts, and IT professionals looking to transition into AI engineering roles. Even learners from non-technical backgrounds can follow the structured, beginner-friendly approach and gain practical skills in building AI applications on Google Cloud.
COMMON QUESTIONS
Skills Covered
FOR Generative AI Engineer
for Generative AI Engineer
Generative AI Engineers design intelligent systems that generate accurate, context-aware responses by combining AI models with enterprise data sources.
Build production-ready RAG applications on Google Cloud
Gain hands-on experience with Vertex AI (Gemini) and Vector Search
Create portfolio-ready projects for job interviews
Earn an industry-recognized GCP AI certification
CERTIFICATION
After finishing Nevolearn's Build RAG on Google Cloud Using Vertex AI 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.
TESTIMONIALS
This Google Cloud RAG course is designed to provide practical Generative AI training for building real-world applications using RAG on GCP. Learners gain hands-on experience with Vertex AI training, working with Gemini AI models to create intelligent, context-aware systems powered by enterprise data.
The course focuses on building an end-to-end RAG pipeline, including document ingestion, embedding generation, and retrieval using Vector Search. You will also integrate structured data with BigQuery AI and design scalable architectures for modern AI app development.
Through guided labs and real-world scenarios, students learn Cloud Run deployment to launch secure, production-ready AI applications. This cloud AI course emphasizes best practices in security, monitoring, and performance optimization, making it ideal for enterprise environments.
As a comprehensive AI engineering course, it prepares learners for advanced roles in enterprise AI training and cloud-based intelligent systems. Upon completion, participants earn a recognized GCP AI certification, validating their expertise in building scalable, enterprise-grade AI solutions on Google Cloud.
Expand your expertise in Generative AI and cloud-based application development with our advanced Google Cloud RAG course. This program helps learners build production-ready AI systems using Vertex AI (Gemini), Vector Search, BigQuery, and Cloud Run for scalable deployment.
Designed for beginners and professionals, this cloud AI training focuses on creating Retrieval-Augmented Generation (RAG) pipelines that combine document ingestion, embedding generation, vector indexing, and grounded response generation. You will gain hands-on experience working with enterprise-grade tools like Cloud Storage, Document AI, and IAM security.
To further strengthen your learning, explore related paths such as Cloud Computing Fundamentals, AI/ML Engineering, and Data Engineering on GCP. These complementary programs enhance your ability to build, secure, and optimize cloud-based AI applications across industries.
Recommended Learning Path:
Cloud Basics → Google Cloud Fundamentals → RAG Systems → Advanced AI/ML Engineering
By following this structured learning path, you can build strong expertise in AI application development, improve career opportunities in cloud AI roles, and become proficient in designing enterprise-ready intelligent systems.
