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MLOPS COURSE IN HYDERABAD

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.

4.9★
Average Rating
1000+
Students Placed
150+
Hiring Partners
100%
Placement Support

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
Live Online Bootcamp
Course Duration
4.5 Months (Approx. 18 Weeks)
Next Cohort starts
02 Mar, 2026

Highlights of Our MLOps Course in Hyderabad

Hands-on MLOps Projects

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

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

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

24/7 Learning Support

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

Main Course Page

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.

No signup required — explore at your own pace

What you'll find on the main page

Full Curriculum

Deep-dive modules covering every topic end to end

Hands-on Projects

Build portfolio-ready apps with real-world datasets

Certification

Industry-recognized certificate on completion

Career Support

Placement prep, mock interviews and resume reviews

Fee and EMI Plans

Transparent pricing with flexible payment options

4.9 Rated

Top-rated by 340+ working professionals across India

Industry-Recognized CertificationLive Mentor-Led SessionsPlacement Assistance4.9 ★ Average Rating

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)

01

Expert-Led Sessions

Learn from mentors who design and operate ML platforms in Hyderabad’s product, cloud, and GCC teams.

02

Built for Working Pros & Career Switchers

Evening/weekend-friendly schedules for data scientists, ML engineers, DevOps/SREs, and developers moving into MLOps.

03

Real-World Assignments

Hands-on with versioned datasets, Airflow DAGs, CI/CD pipelines, K8s model serving, and blue/green rollouts.

04

1:1 Mentor Hours & Doubt Clearing

Get unstuck quickly with mentor sessions, code reviews, and responsive Slack/forum support.

05

AI-Focused Mock Interviews

10+ mock rounds simulating Hyderabad hiring panels—platform design, failure scenarios, and cost vs SLA trade-offs.

06

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

1

Foundation

  • Core concepts
  • Tools & setup
  • Hands-on intro
2

Build

  • Advanced techniques
  • Guided projects
  • Industry tools
3

Specialise

  • Elective tracks
  • Capstone project
  • Peer reviews
4

Launch

  • Portfolio prep
  • Mock interviews
  • Placement drive

Skills You Will Command

MLflow & Experiment TrackingAirflow & Kubeflow PipelinesDocker, Kubernetes & HelmAzure ML, AWS SageMaker, GCP Vertex AITorchServe, Ray Serve, FastAPICI/CD: Jenkins & GitHub ActionsPrometheus & Grafana MonitoringData & Model Drift, LineageSecurity (IAM, Secrets) & FinOps

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.

Certificate of Completion

Issued by School of Core AI upon successful completion of the programme

Top Companies Hiring for MLOps in Hyderabad

Microsoft – Azure ML Ops hiring
Amazon – AWS SageMaker, ML infra roles
Google – Vertex AI & TensorFlow Ops
Qualcomm – AI model deployment at scale
Deloitte – MLOps consulting practices
Accenture – Enterprise ML pipelines
NVIDIA – ML platform automation
ServiceNow – AI infra engineering
HSBC Tech – BFSI AI/ML Ops hiring
Tech Mahindra – Data & ML platform ops
ValueLabs – MLOps for SaaS products
Genpact – AI/ML engineering hiring
Capgemini – Cloud ML pipelines
Wells Fargo – Risk AI with MLOps
Infosys – AI platforms & ML lifecycle

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.

1
Experiment tracking with MLflow and model registries
2
Pipeline orchestration using Airflow and Kubeflow
3
Containerization & scalable deployment with Docker and Kubernetes
4
Cloud MLOps on Azure ML, AWS SageMaker, and GCP Vertex AI
5
Model serving with TorchServe, Ray Serve, REST & gRPC APIs
6
Data & model drift detection with contracts and lineage tracking
7
Observability with Prometheus, Grafana, and alerting pipelines
8
Security practices — secrets management, IAM, and supply chain
9
Cost & performance optimization (FinOps for ML workloads)

Explore Related Tracks

Upskill across adjacent domains to grow into platform leadership roles.

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

Single transparent fee covering complete training, real-world projects, certification and placement support. EMI and part-payment options are available with our counsellor.

Total Course Fee
60,000

Final fee, EMI plans and any ongoing offers will be confirmed by your counsellor based on your batch, mode and payment preference.

Your Career Path after MLOps

AI Platform Engineer

Scale infra & tooling

LLMOps Specialist

Productionize LLMs

Engineering Manager (AI)

Lead ML Platform teams

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.
SK
Sanjana K.
MLOps Engineer
Exactly the push I needed to go from ML notebooks to production. Kubeflow, Docker, and Helm deployments were the highlight.
HV
Harish V.
ML Engineer → Platform
Loved the mock interviews—lots of failure-mode and rollout questions, just like Hyderabad product teams.
SP
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.
AD
Anusha D.
MLOps Associate
I’m from a DevOps background. This course helped me translate my skills to ML platforms with confidence and structure.
RT
Ravi Teja
DevOps → MLOps
Great mentor support and code reviews. My serving pipeline now has observability and cost controls thanks to this program.
MS
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.