School of core ai logo
whatsapp
whatsappChat with usphoneCall us

MLOPS COURSE IN HYDERABAD

School of Core AI - Data Science Course

Advance your ML career with Hyderabad’s leading MLOps Course. Master CI/CD pipelines, containerized model serving, and cloud MLOps on Azure, AWS & GCP. Certification and placement support with top AI and product teams in HITEC City and Gachibowli.

Book a Demo

Key Learning Highlights in Hyderabad’s MLOps Course

200+

Hyderabad professionals
upskilled in MLOps

Evening & Weekend

Flexible live sessions
tailored for working talent

8+ Projects

End-to-end builds on CI/CD, pipelines, serving & monitoring
with real-world datasets

Placement Assistance

Mock interviews, resume support, and
recruiter referrals in Hyderabad’s AI ecosystem

Learning format
Learning Format
Live Online Bootcamp
Course duration
Course Duration
4.5 Months (Approx. 18 Weeks)
Next cohort
Next Cohort starts
27 Oct, 2025

Highlights of Our MLOps Course in Hyderabad

Hands-on MLOps Projects
Hands-on MLOps Projects

Track experiments with MLflow, orchestrate pipelines via Airflow/Kubeflow, and deploy using Docker & Kubernetes.

Cloud-Native Deployments
Cloud-Native Deployments

Practice on Azure ML, AWS SageMaker, and GCP Vertex AI with Infrastructure-as-Code (Terraform) for real-world automation.

Hyderabad Hiring Network
Hyderabad Hiring Network

Curriculum aligned to roles at Microsoft, Amazon, Google, Deloitte, Wells Fargo, Qualcomm, NVIDIA, Novartis, and GCCs in the Financial District.

24/7 Learning Support
24/7 Learning Support

Live doubt clearing, mentor reviews, and strong community support to keep your builds on track.

Check Out the Full MLOps Course Curriculum

This Hyderabad page gives you a local view. Explore the complete MLOps curriculum, tools, projects, and certifications on our main course page.

See Full Curriculum & Certification

Why Learn MLOps in Hyderabad’s Cloud & GCC Capital?

Hyderabad has become India’s cloud and GCC powerhouse, with Microsoft, Google, Amazon, Deloitte, HSBC, and TCS running massive AI/ML operations here. These teams urgently need engineers who can take ML from notebooks to production with security, scalability, and compliance.
Our MLOps course bridges data science and DevOps so you can build automated ML pipelines, deploy containerized models, and monitor them in production. Master the full toolchain—MLflow, Airflow, Kubeflow, Docker, Kubernetes, Azure ML, AWS SageMaker, and GCP Vertex AI—guided by practitioners actively operating these stacks across HITEC City and Gachibowli.

Why SCAI’s MLOps Course in Hyderabad Stands Out

Compare our production-focused MLOps training with typical ML courses in Hyderabad

Feature
Learning Format
School of Core AI

Live online with mentor code reviews & project clinics

Other Institutes

Recorded videos with limited interaction

Feature
Curriculum Depth
School of Core AI

Covers pipelines, serving, cloud, observability & governance

Other Institutes

Focus on modeling only—no production coverage

Feature
Projects & Case Studies
School of Core AI

8+ real projects including CI/CD, K8s, and canary rollouts

Other Institutes

Mini-projects not aligned to platform realities

Feature
Cloud Coverage
School of Core AI

Azure ML, AWS SageMaker, and GCP Vertex AI hands-on

Other Institutes

Single-cloud demos only

Feature
Placement Support
School of Core AI

Hyderabad-focused referrals & mock panels

Other Institutes

Generic job portal guidance

Feature
Certification
School of Core AI

Industry-recognized MLOps certificate

Other Institutes

Basic completion certificate

Placement-Focused MLOps Training (Live Online)

Expert-Led Sessions
Learn from mentors who design and operate ML platforms in Hyderabad’s product, cloud, and GCC teams.
Built for Working Pros & Career Switchers
Evening/weekend-friendly schedules for data scientists, ML engineers, DevOps/SREs, and developers moving into MLOps.
Real-World Assignments
Hands-on with versioned datasets, Airflow DAGs, CI/CD pipelines, K8s model serving, and blue/green rollouts.
1:1 Mentor Hours & Doubt Clearing
Get unstuck quickly with mentor sessions, code reviews, and responsive Slack/forum support.
AI-Focused Mock Interviews
10+ mock rounds simulating Hyderabad hiring panels—platform design, failure scenarios, and cost vs SLA trade-offs.
Career & Placement Support
Resume/portfolio reviews, interview prep, and recruiter referrals targeted at HITEC City, Gachibowli, and the Financial District.

MLOps Course in Hyderabad

Deploy AI the GCC Way — MLOps Skills for Hyderabad’s Cloud & Captive Tech Teams
Hyderabad is India’s cloud and GCC powerhouse. This course trains you on MLflow, Kubeflow, Airflow, Docker, Kubernetes, Azure ML, AWS SageMaker, and GCP Vertex AI — the exact stack demanded by GCCs and product firms across HITEC City and Gachibowli.

What You’ll Learn in the MLOps Course

01
Pipelines & Experimentation
Master experiment tracking (MLflow), reproducibility, data/version control, and orchestration with Airflow & Kubeflow.
02
Serving & Scaling
Package models with Docker, serve via TorchServe/Ray Serve, and scale using Kubernetes/Helm with canary and blue–green strategies.
03
Cloud MLOps
Deploy on Azure ML, AWS SageMaker, and GCP Vertex AI; apply Terraform, manage secrets, roles, and policies securely.
04
Observability & Governance
Set up monitoring (Prometheus/Grafana), detect drift, ensure fairness & lineage, and implement cost controls.

MLOps Learning Roadmap: From Zero to Production

Skills You Will Command

MLflow & Experiment Tracking
Airflow & Kubeflow Pipelines
Docker, Kubernetes & Helm
Azure ML, AWS SageMaker, GCP Vertex AI
TorchServe, Ray Serve, FastAPI
CI/CD: Jenkins & GitHub Actions
Prometheus & Grafana Monitoring
Data & Model Drift, Lineage
Security (IAM, Secrets) & FinOps
MLflow & Experiment Tracking
Airflow & Kubeflow Pipelines
Docker, Kubernetes & Helm
Azure ML, AWS SageMaker, GCP Vertex AI
TorchServe, Ray Serve, FastAPI
CI/CD: Jenkins & GitHub Actions
Prometheus & Grafana Monitoring
Data & Model Drift, Lineage
Security (IAM, Secrets) & FinOps
Enquire Now : +91 96914 40998

Industry-Recognized MLOps Certification (Hyderabad)

On completion, earn a certification recognized by hiring teams across Hyderabad’s GCCs and product companies, validating your ability to ship reliable ML to production.
data analytics for ai certificate

Top Companies Hiring for MLOps in Hyderabad

MLOps Career Opportunities in Hyderabad’s Tech Market

Hyderabad’s cloud-first and GCC-heavy ecosystem is driving rapid demand for MLOps talent.

Roles
  • MLOps Engineer 26–31%
  • Machine Learning Engineer 22–26%
  • Data Scientist 18–22%
  • AI Platform Engineer 12–16%
  • Cloud ML Engineer 8–12%
MLOps Engineer

Design CI/CD for ML, containerize models, automate deployments, and monitor SLAs. Share: 26–31%, Median CTC: ₹17–28 LPA.

Machine Learning Engineer

Build/optimize models and integrate them with production services and feature stores. Share: 22–26%, Median CTC: ₹15–25 LPA.

AI Platform Engineer

Scale platform primitives—feature stores, registries, infra APIs—for large GCC/product teams. Share: 12–16%, Median CTC: ₹18–30 LPA.

In-Demand MLOps Skills

Skills recruiters look for when hiring modern MLOps engineers.

Experiment tracking with MLflow and model registries
Experiment tracking with MLflow and model registries
Pipeline orchestration using Airflow and Kubeflow
Pipeline orchestration using Airflow and Kubeflow
Containerization & scalable deployment with Docker and Kubernetes
Containerization & scalable deployment with Docker and Kubernetes
Cloud MLOps on Azure ML, AWS SageMaker, and GCP Vertex AI
Cloud MLOps on Azure ML, AWS SageMaker, and GCP Vertex AI
Model serving with TorchServe, Ray Serve, REST & gRPC APIs
Model serving with TorchServe, Ray Serve, REST & gRPC APIs
Data & model drift detection with contracts and lineage tracking
Data & model drift detection with contracts and lineage tracking
Observability with Prometheus, Grafana, and alerting pipelines
Observability with Prometheus, Grafana, and alerting pipelines
Security practices — secrets management, IAM, and supply chain
Security practices — secrets management, IAM, and supply chain
Cost & performance optimization (FinOps for ML workloads)
Cost & performance optimization (FinOps for ML workloads)

Explore Related Tracks

Upskill across adjacent domains to grow into platform leadership roles.

✨

Generative AI (RAG & Agents)

📘

Data Engineering

📘

LLMOps

📘

AIOps

Our Vibrant Student Community

Hyderabad learners collaborate on capstones, share interview tips, and review pipelines together—accelerating growth into platform teams.

Benefits of Our MLOps Community

Code Reviews & Pairing
Code Reviews & Pairing
Access to Templates & IaC
Access to Templates & IaC
Hiring Referrals & Mock Panels
Hiring Referrals & Mock Panels
Mentorship from Platform Engineers
Mentorship from Platform Engineers
Career Growth Playbooks
Career Growth Playbooks
Alumni work across Hyderabad’s GCCs and product teams in HITEC City, Gachibowli, and the Financial District.

Our Alumni Network

MLOps Course Fees in Hyderabad

Transparent pricing with certification and placement support included.
One-time Plan
₹72,999
One-time payment covering complete training, certification, and placement assistance.
Your Career Path after MLOps
MLOps Engineer

Start here

Explore
CurriculumFeesPlacementProjects
AI Platform Engineer

Scale infra & tooling

Explore
CurriculumFeesPlacementProjects
LLMOps Specialist

Productionize LLMs

Explore
CurriculumFeesPlacementProjects
Engineering Manager (AI)

Lead ML Platform teams

Explore
CurriculumFeesPlacementProjects
Swipe to see all steps →
Explore related paths
MLOps EngineerAI Platform EngineerLLMOps SpecialistEngineering Manager (AI)

Testimonials of Our Successful Learners

I moved from data analysis to MLOps within 5 months. The Azure ML + Airflow modules matched my team’s stack in HITEC City.
amit-joshi
Sanjana K.
MLOps Engineer
Exactly the push I needed to go from ML notebooks to production. Kubeflow, Docker, and Helm deployments were the highlight.
amit-joshi
Harish V.
ML Engineer → Platform
Loved the mock interviews—lots of failure-mode and rollout questions, just like Hyderabad product teams.
amit-joshi
Saif P.
AI Platform Engineer
The capstone covered MLflow, Airflow, and K8s serving end-to-end. That portfolio piece helped me crack a GCC interview.
amit-joshi
Anusha D.
MLOps Associate
I’m from a DevOps background. This course helped me translate my skills to ML platforms with confidence and structure.
amit-joshi
Ravi Teja
DevOps → MLOps
Great mentor support and code reviews. My serving pipeline now has observability and cost controls thanks to this program.
amit-joshi
Mahima S.
Cloud ML Engineer

Frequently Asked Questions

The MLOps course runs for about 4.5 months. You’ll attend live online classes, work on real projects, and get access to mentor-led mock interviews—all scheduled to fit a working professional’s routine.