GRRAS — 15+ Years as a Trusted Training Partner of Red Hat & Linux Foundation
Master MLOps, AI & DevOps to build, deploy, automate and scale production-ready AI systems — with a 12-month career journey designed to take you from learning to employment.
We are rated 4.8 out of 5
Join over 25,000 students who have trusted GRRAS to build successful technology careers. Our industry-focused training, practical learning, and career support help students grow in AI, DevOps, Cloud, and MLOps.
DevOps + MLOps + AI
Portfolio + Capstone Projects
Structured Career Journey
Real Internship Experience
Minimum CTC Guarantee*
A structured 12-month pathway designed for one single goal: getting you placed. We blend intense technical training with practical experience to build a guaranteed career path.
280 hours of hands-on training mastering AI, DevOps, Cloud, and Kubernetes fundamentals.
Turn learning into proof. Build 13 production-ready Portfolio & Capstone projects.
4 months of real internship experience alongside intense mock interviews and resume building.
Complete the programme with internship experience and active placement support. Eligible students receive our Job Guarantee until they secure a minimum ₹3 LPA CTC.
*The 100% Job Guarantee is subject to eligibility criteria, student participation requirements, and the official enrolment agreement.
A complete, professionally guided roadmap into DevOps, Cloud, and AI Engineering, culminating in an industry job offer.
Building an ML model is only the beginning. Companies need professionals who can:
Transition models from local notebooks to scalable, production-ready APIs and endpoints.
Eliminate manual handoffs by orchestrating data extraction, training, and evaluation pipelines.
Implement continuous integration and delivery to test, version, and release models safely.
Leverage AWS, GCP, or Azure to provision scalable compute resources for training and inference.
Package models and dependencies using Docker to ensure consistent environments everywhere.
Orchestrate containers with K8s for high availability, auto-scaling, and self-healing deployments.
Track model drift, data quality, and system performance metrics in real-time.
Ensure reproducibility, governance, and seamless rollbacks for enterprise-grade AI applications.
Learn the complete connection. Find the perfect financing solution tailored to your needs.
Most programmes stop after training. This programme continues for 12 months — because becoming job-ready requires more than completing a syllabus.
Technical Training
Interview Bootcamp
Internship & Placement
We design this path to take you from a learner to an earner. It’s not just about skills; it’s about breaking into the industry effectively.
The brochure specifically describes this journey as Training → Prep → Internship → Offer. We ensure you are fully equipped and placed into the real world.
The programme describes the core curriculum as 280 hours across 19 phases covering DevOps, Cloud and Agentic AI, with hands-on labs and production-grade projects.
Linux, Git, Docker, CI/CD, Jenkins, Infrastructure & automation practices.
Cloud infrastructure, Deployment, Scalability, and automation.
ML pipelines, Automation, Model lifecycle, Monitoring.
AI fundamentals, Generative AI concepts, AI-powered workflows, and building autonomous Agentic AI systems.
Containers, Kubernetes fundamentals, Deployment, Scaling, Production environments.
This programme is tailored for dedicated individuals looking to build a serious career. It is ideal for serious freshers who are:
It's a comprehensive career transformation programme designed to take you from a learner to a production-ready professional.
Don't just say "I have done a project." Confidently explain what you built, why you built it, how you deployed it, and how you would run it in production.
Forget checklist projects. Demonstrate problem-solving, AI/ML workflows, cloud infrastructure, and deployment. Projects are mentor-reviewed across code, architecture, and production discipline.
Go through 4–5 structured mock interview cycles—one every 45 days. Receive detailed feedback on technical knowledge, troubleshooting, scenario-based questions, and communication.
A dedicated 4-week sprint: Week 1 (Resumes & GitHub), Week 2 (System Design & Tech), Week 3 (HR & Behavioural), and Week 4 (Offer Readiness & Salary Negotiation).
Whether you're looking for a solid foundation or a guaranteed career outcome, we have a plan that fits.
For learners wanting a self-paced, solid foundation in AI and MLOps.
What's included:
For dedicated learners seeking comprehensive support and an assured outcome.
Included everything in Standard, plus:
*₹3 LPA Minimum CTC Guarantee is subject to eligibility criteria, strict adherence to the attendance policy, and successful completion of all milestone evaluations and projects.
Our experts have helped thousands of students enhance their technical skills and achieve their career goals.
"RHCSA RHCE OpenShift Certified"
"RHCSA RHCE Certified"
"Data Scientist "
"Soft-Skills and Communications Skills Trainer"
"Docker Kubernates Certified Trainer"
"Placement Coordinator"
"RHCA, AWS, Openshift, DevsecOps Certified"
"RHCA Level 5"
Learn the intersection of AI and modern DevOps.
Training doesn't stop when the classes end.
Build projects you can confidently discuss in interviews.
Practice before facing the real thing.
Learn to communicate your technical skills professionally.
One complete month focused on converting skills into interview performance.
Gain practical workplace experience.
A team actively works towards your placement.
Your progress is tracked throughout the journey.
Subject to official eligibility terms.
*Terms & Conditions Apply
Build skills relevant to top-tier industry roles. Here are the positions you will be prepared for:
Build and operate ML systems in production.
Automate infrastructure, deployment and CI/CD.
Build and manage scalable cloud environments.
Develop and deploy AI-powered applications.
Build and operationalise machine learning workflows.
Companies visit GRRAS to connect with skilled professionals prepared for opportunities in Linux, Cloud, DevOps and modern IT technologies. Through practical training and hands-on learning, GRRAS helps learners develop job-ready technical skills that employers look for.
Technologies and engineering ecosystems shaping modern infrastructure
Build skills relevant to modern DevOps, Cloud and AI-powered engineering workflows.
Don't replace your DevOps skills. Upgrade them with AI and prepare to work with intelligent infrastructure, AI-powered automation and modern cloud environments.
Here are some common questions about our programme to help you understand better.
MLOps combines Machine Learning with DevOps practices to build, deploy, automate, monitor and scale ML systems in production.
Yes. The Career Guarantee track is designed specifically for serious freshers who meet the stated eligibility criteria.
