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MLOPS COURSE IN BANGALORE

School of Core AI - Data Science Course

Advance your ML career with Bangalore’s most industry-focused MLOps Course. Learn to build reproducible ML pipelines, automate CI/CD workflows, and deploy models at scale using AWS, Azure, and GCP. Designed for freshers and working professionals, the program includes certification and placement support with top AI and data teams in Bengaluru.

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Perks of Joining Our MLOps Course in Bangalore

250+

Professionals in Bangalore
upskilled in MLOps

Evening & Weekend

Flexible live online batches
designed for working professionals

8+ Projects

Hands-on builds with MLflow, Kubeflow, Airflow, CI/CD & monitoring

Placement Assistance

Mock interviews, resume building
and recruiter referrals in Bangalore

Learning format
Learning Format
Live Online Bootcamp
Course duration
Course Duration
4.5 months (approx. 18 weeks)
Next cohort
Next Cohort starts
29 Sept, 2025

Highlights of Our MLOps Course in Bangalore

Hands-on MLOps Projects
Hands-on MLOps Projects

Implement tracking with MLflow, orchestrate pipelines with Airflow/Kubeflow, and deploy with Docker & Kubernetes.

Cloud-Native Deployments
Cloud-Native Deployments

Practice on AWS SageMaker, Azure ML, and GCP Vertex AI with IaC patterns for real infra.

Bangalore Hiring Network
Bangalore Hiring Network

Alignment with roles at Infosys, Wipro, TCS, Flipkart, Swiggy, Razorpay, Meesho, and AI platform teams.

24/7 Learning Support
24/7 Learning Support

Get timely help from mentors and a dedicated support team throughout your builds.

Check Out the Full MLOps Course Curriculum

This Bangalore 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 Bengaluru’s Product & Platform Scene?

Bengaluru teams need engineers who can move models from notebooks to real users. This MLOps course bridges data science and DevOps so you can ship reliable, monitored ML at scale.
From unicorns to global captives, Bengaluru companies expect automated pipelines, robust model serving, observability, and cost control. Learn the exact toolchain—MLflow, Airflow/Kubeflow, Docker, Kubernetes, AWS SageMaker, Azure ML, and GCP Vertex AI—guided by engineers who run these stacks in production.

What Makes Our MLOps Course in Bangalore Different

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

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

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

Other Institutes

Single-cloud demos only

Feature
Placement Support
School of Core AI

Bengaluru-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
Expert-Led Sessions
Learn directly from mentors who design and operate ML platforms at Bengaluru’s leading product, fintech, and SaaS firms.
Built for Working Pros & Career Switchers
Built for Working Pros & Career Switchers
Evening and weekend-friendly schedules designed for data scientists, ML engineers, DevOps/SREs, and software developers transitioning into MLOps.
Real-World Assignments
Real-World Assignments
Hands-on work with versioned datasets, Airflow DAGs, CI/CD pipelines, containerized model serving, and blue/green rollout strategies.
1:1 Mentor Hours & Doubt Clearing
1:1 Mentor Hours & Doubt Clearing
Get unstuck quickly with scheduled one-on-one mentor sessions, detailed code reviews, and active Slack/forum support.
AI-Focused Mock Interviews
AI-Focused Mock Interviews
Prepare with 10+ mock rounds that simulate real hiring panels—covering platform design, failure scenarios, and cost vs SLA trade-offs.
Career & Placement Support
Career & Placement Support
Receive personalized resume feedback, portfolio reviews, and recruiter referrals targeted at Bengaluru’s MLOps and AI hiring market.

MLOps Course in Bangalore

Build, Ship, and Scale ML in Production — The Bengaluru Way
Master the full MLOps lifecycle with tools like MLflow, Airflow, Kubeflow, Docker, Kubernetes, AWS SageMaker, Azure ML, and GCP Vertex AI. Designed for Bengaluru’s product, fintech, and AI platform teams that demand production-ready ML pipelines.

What You’ll Learn in the MLOps Course

01
Pipelines & Experimentation
Master experiment tracking with MLflow, reproducibility, data/version control, and pipeline orchestration using Airflow and Kubeflow.
02
Serving & Scaling
Package models with Docker, serve with TorchServe or Ray Serve, and scale using Kubernetes/Helm with canary and blue-green rollout strategies.
03
Cloud MLOps
Deploy end-to-end ML systems on AWS SageMaker, Azure ML, and GCP Vertex AI. Implement infra-as-code, manage secrets, roles, and policies securely.
04
Observability & Governance
Set up monitoring with Prometheus/Grafana, detect data & concept drift, ensure fairness & lineage tracking, and apply cost-control mechanisms.

MLOps Learning Roadmap: From Zero to Production

Skills You Will Command

MLflow & Experiment Tracking
Airflow & Kubeflow Pipelines
Docker, Kubernetes & Helm
AWS SageMaker, Azure ML, Vertex AI
TorchServe, Ray Serve, FastAPI
CI/CD with Jenkins & GitHub Actions
Monitoring: Prometheus & Grafana
Data & Model Drift, Lineage
Security, Secrets, IAM & Cost Control
MLflow & Experiment Tracking
Airflow & Kubeflow Pipelines
Docker, Kubernetes & Helm
AWS SageMaker, Azure ML, Vertex AI
TorchServe, Ray Serve, FastAPI
CI/CD with Jenkins & GitHub Actions
Monitoring: Prometheus & Grafana
Data & Model Drift, Lineage
Security, Secrets, IAM & Cost Control
Enquire Now : +91 9997800680

Industry-Recognized MLOps Certification (Bengaluru)

Complete the program and earn an industry-recognized certificate that validates your ability to ship reliable ML to production—trusted by hiring teams across Bengaluru.
data analytics for ai certificate

Top Companies Hiring for MLOps in Bangalore

Career Opportunities in MLOps – Bangalore

MLOps roles are among the fastest-growing in Bengaluru as teams productize ML at scale.

Roles
  • MLOps Engineer 28–32%
  • Machine Learning Engineer 22–26%
  • Data Scientist 18–22%
  • AI Platform Engineer 12–16%
  • Cloud ML Engineer 8–12%
MLOps Engineer

Design CI/CD pipelines, containerize models, automate deployments, and monitor SLAs. Share: 28–32%, Median CTC: ₹18–30 LPA.

Machine Learning Engineer

Train/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 thousands of ML users. Share: 12–16%, Median CTC: ₹20–32 LPA.

In-Demand MLOps Skills in Bangalore

What Bengaluru hiring managers expect from modern MLOps engineers.

MLflow tracking, model registry & artifacts
MLflow tracking, model registry & artifacts
Airflow/Kubeflow orchestration & retries
Airflow/Kubeflow orchestration & retries
Docker images, K8s deployments, Helm charts
Docker images, K8s deployments, Helm charts
AWS SageMaker, Azure ML, Vertex AI patterns
AWS SageMaker, Azure ML, Vertex AI patterns
TorchServe/Ray Serve, REST & gRPC serving
TorchServe/Ray Serve, REST & gRPC serving
Drift detection, data contracts & lineage
Drift detection, data contracts & lineage
Prometheus/Grafana monitoring & alerting
Prometheus/Grafana monitoring & alerting
Secrets, IAM, policies & supply-chain security
Secrets, IAM, policies & supply-chain security
FinOps for ML — optimize cloud cost & latency
FinOps for ML — optimize cloud cost & latency

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

Bengaluru 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 in Bengaluru’s product, fintech, and platform teams across unicorns and global captives.

Our Alumni Network

MLOps Course Fees in Bangalore

Transparent pricing with certification and placement support included.
One-time Plan
₹74,999
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

Came in as a data analyst. Left with a production-ready ML pipeline and a new job title. The Airflow + MLflow stack prepared me for real Bengaluru interviews.
amit-joshi
Harshitha N.
MLOps Engineer
Exactly the bridge I needed from ML modeling to deployment. The Kubernetes, Helm, and monitoring parts were gold.
amit-joshi
Akash R.
ML Engineer → Platform
Hands-on exposure to SageMaker and Azure ML helped me align with my company’s stack. Landed an internal move in 4 months.
amit-joshi
Suhani K.
Cloud ML Engineer
Loved the mock interviews—deep questions on failure modes, rollbacks, and cost control. Felt just like Bengaluru product teams.
amit-joshi
Rohit P.
AI Platform Engineer
The capstone used MLflow, Airflow, and TorchServe end-to-end. That portfolio piece got me shortlisted at two fintechs.
amit-joshi
Vikas G.
MLOps Associate
I’m from a DevOps background. This course helped me translate my skills to ML platforms with confidence.
amit-joshi
Tanvi S.
DevOps → MLOps

Frequently Asked Questions

The program runs for ~4.5 months with live online classes, projects, and mock interviews scheduled for working professionals.