AI & DATA

MLOps & AI Engineering

Operationalize machine learning with automated CI/CD retraining pipelines, feature stores, drift detection, and high-performance model serving.

6 Months 150+ Hours Live + Hands-on Production ML Aligned
MLOps & AI Engineering practical training
6 Months
Instructor-led program
IBM
Learning ecosystem access
Microsoft
Learning ecosystem access
Projects
Hands-on portfolio
Credentials
Credential pathways
Internship*
6-month paid internship

What You Will Learn

Structured curriculum designed for practical, job-ready skills.

01
ML Engineering Foundations
Python, ML lifecycle & reproducible experiments
02
Model Development
Training, evaluation, feature pipelines & tracking
03
MLOps
MLflow, model registry, versioning & deployment workflows
04
Cloud AI Deployment
Containers, APIs, cloud ML services & inference
05
LLMOps & Monitoring
LLM evaluation, monitoring, drift & observability
06
Production AI Capstone
Deploy an end-to-end AI service with CI/CD

Tools & Technologies

Hands-on enterprise stack used across the program.

Python
Hands-on
MLflow
Hands-on
Docker
Hands-on
Kubernetes
Hands-on
GitHub Actions
Hands-on
AWS
Hands-on
Azure
Hands-on
Prometheus
Hands-on

Production Capstone Projects

Build a portfolio of enterprise-grade projects evaluated by working tech leaders.

CI/CD for ML

Zero-Downtime Model Continuous Retraining Pipeline

Automated GitOps pipeline that triggers training on data drift, registers model artifacts, and deploys canary containers.

MLflowGitHub ActionsDockerKubernetes
Feature Store

Enterprise Real-Time Feature Store Implementation

Centralized feature registry supplying sub-millisecond online inference features and consistent offline training datasets.

FeastRedisPostgreSQLPython
Observability

Model Performance & Concept Drift Telemetry Hub

Production monitoring dashboard visualizing prediction drift, Kolmogorov-Smirnov statistics, and latency degradation.

Evidently AIPrometheusGrafanaFastAPI
Serving at Scale

High-Performance GPU-Optimized Triton Inference Server

Dynamic batching model serving architecture handling concurrent vision and NLP workloads under 20ms p99.

TritonDockerFastAPIKubernetes

Career Opportunities & Outcomes

Prepare for top-tier roles across our 500+ corporate recruitment partners.

Target Salary Range: ₹10 - 28 LPA

High-Demand Career Tracks:

Senior MLOps & AI Engineering EngineerMLOps & AI Engineering ArchitectMLOps & AI Engineering ConsultantLead Production EngineerPlatform SpecialistCloud Solutions Specialist

Frequently Asked Questions

Everything you need to know about admissions, curriculum, and internships.

This program is beginner-friendly and starts from fundamental core principles before advancing to production-grade enterprise implementations. Prior exposure to basic computing or programming is helpful but not mandatory.

Upon fulfilling course benchmarks and capstone assessments, you are placed into a guaranteed 6-month corporate paid internship offering ₹15,000–₹25,000 per month stipend (totaling ₹90,000 to ₹1,50,000 in stipend earnings) with verified corporate experience letters.

You will earn official credentials and digital badges aligned with Production ML Aligned, alongside an official AI Campus Certificate of Mastery that is verifiable on LinkedIn and recognized by 500+ corporate hiring partners.

The program fee of ₹80,000 (inclusive of GST) can be paid via 0% interest no-cost EMI starting from ₹6,666/month with zero down payment required.

Graduates qualify for high-growth roles in AI & Data with corporate salary packages typically spanning from ₹10 - 28 LPA, backed by our dedicated 100% placement support team.

🎓 1-on-1 Senior Engineering Mentorship

Confused about your career path? Don't wait — talk directly to a mentor.

Get transparent, personalized guidance on curriculum, eligibility, scholarship waivers, and the guaranteed ₹15,000–₹25,000 monthly internship stipend. No sales pressure — just honest advice from working tech leaders.

15-Min Free Strategy Call Profile & Resume Review Personalized Learning Roadmap
⚡ Next batch starts soon • Limited 30 seats

Learn from Global Technology Ecosystems

Dedicated learning access and credential pathways through applicable IBM and Microsoft programs.

Learning access • Skills • Credentials
Microsoft Learning access • Applied skills • Credentials