+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.
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 training empowers professionals to build secure, enterprise-ready Generative AI systems using Google managed services. Learners move beyond simple chatbot experimentation and gain practical expertise in designing ingestion pipelines, generating embeddings, configuring vector search, implementing retrieval-based grounding, and deploying scalable AI assistants within GCP environments.
For individuals, this certification enhances career prospects in Google Cloud-based Generative AI roles and builds a strong portfolio project that demonstrates real-world implementation capability. It prepares learners for cloud AI job roles where grounded AI systems are preferred over standalone prompt-only solutions.
For organizations, trained professionals can build internal AI assistants connected to enterprise knowledge bases, improving productivity, reducing manual support workload, and ensuring compliance with security and access governance policies
