Certified MLOps Engineer

Target audience

• Professionals and graduates building a career in this field.
• Career switchers and upskillers.

Overview

A project-based, 40-hour professional certification (Certified MLOps Engineer) built around real roles and a hands-on technical stack.

Description

Covers: MLOps lifecycle · Docker · API deploy · Kubernetes · CI/CD · MLflow · serving · monitoring.

Learning objectives

• Build job-ready skills across the full technical stack.
• Apply each concept in hands-on labs and projects.
• Produce a portfolio-ready capstone.

Detailed outline

1. MLOps lifecycle
2. Docker
3. API deploy
4. Kubernetes
5. CI/CD
6. MLflow
7. serving
8. monitoring

Projects & workshops

• Hands-on labs throughout the program (70% project-based).
• A capstone project demonstrating end-to-end skills.

Outcomes

• Earn the CMOE certification and a portfolio of projects.
• Be ready for role-based work in industry.

Certificate

Globally accredited certificate issued by Epsilon AI Academy — USA, with a unique Certificate ID and EPSILON ID. Awarded on 80% attendance, 80% final exam, and a capstone project.