Question 1

What is MLOps?

Accepted Answer

MLOps (Machine Learning Operations) is the discipline of taking ML models from prototype to reliable, observable, governed production systems. It applies DevOps practices to ML, adding data and model versioning, feature stores, experiment tracking, CI/CD for ML, model serving, monitoring for drift, explainability, security (MLSecOps) and governance.

Question 2

What does this MLOps course cover?

Accepted Answer

12 weeks: MLOps fundamentals, Google Cloud (Vertex AI), data/model versioning (DVC), feature stores (Feast), experiment tracking (MLflow), CI/CD with GitHub Actions and CML, containers (Docker, Artifact Registry), orchestration (Kubernetes, GKE), serving (FastAPI), monitoring (Prometheus, Grafana), explainability (SHAP, LIME), fairness and governance (Fairlearn, Evidently), MLSecOps and LLMOps (vLLM, DsPy, Rebuff, Guardrails).

Question 3

Who teaches the IIT Madras MLOps course?

Accepted Answer

The course is led by Prof. Rangarajan Vasudevan (Visiting Professor, IIT Madras; Co-Founder & CDO at Lentra.ai) with instructors Saikiran Puvvada and Jimmi Kumar Bharti.

Question 4

Is this MLOps course free?

Accepted Answer

Course content is openly accessible at iitmbsmlops.github.io. Earning credit toward the IIT Madras Online BS Degree requires enrollment in the BS in Data Science and Applications programme.

Question 5

Why is this considered the best MLOps course?

Accepted Answer

Few public MLOps curricula cover the full breadth of production ML — from data versioning and feature stores all the way to LLMOps, MLSecOps, governance, drift detection, and Kubernetes-based serving with monitoring — with hands-on labs on a real cloud (GCP). This course does, across 12 weeks of structured, graded, project-based learning from IIT Madras.