Certified MLOps Engineer
A 40-hour certification that turns trained models into reliable production services — packaging, deploying, scaling and monitoring ML with modern MLOps tooling. It bridges data science and operations so models keep delivering value after the notebook, through reproducible pipelines and automated delivery.
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Course Info
- Type
- Certification
- Subject
- Individual & Professional Certification
- Duration
- 40 hours
- Course code
- CMOE
- Prerequisites
- Basic computer literacy; no advanced prerequisites.
Delivery
- Live-virtual — Instructor-led online cohorts.
- On-site — In-person at your premises or ours.
Tools
- MLOps lifecycle
- Docker
- API deploy
- Kubernetes
- CI/CD
- MLflow
- serving
- monitoring
What you'll learn
A 40-hour certification that turns trained models into reliable production services — packaging, deploying, scaling and monitoring ML with modern MLOps tooling. It bridges data science and operations so models keep delivering value after the notebook, through reproducible pipelines and automated delivery.
Working hands-on with Docker, Kubernetes, CI/CD and MLflow, you build the full delivery path for a model: containerize it, expose it as an API, automate its release, and watch it in production. Every module ends in practical labs, and the program closes with a capstone that deploys and monitors a live model.
- ML engineers and data scientists moving models into production.
- DevOps and backend engineers adding ML delivery to their skillset.
- Containerize and serve machine-learning models as production APIs.
- Build automated CI/CD pipelines for model delivery.
- Orchestrate and scale services with Docker and Kubernetes.
- Track experiments and manage model versions with MLflow.
- Monitor models in production and detect drift for retraining.
- Hands-on labs throughout the program (70% project-based).
- A capstone project demonstrating end-to-end skills.
- Package, deploy and serve models with Docker, Kubernetes and CI/CD.
- Track experiments and monitor models in production with MLflow.
Globally accredited certificate issued by Epsilon AI Learning — USA, with a unique Certificate ID and EPSILON ID. Awarded on 80% attendance, 80% final exam, and a capstone project.
Program Curriculum
- The MLOps lifecycle: from experiment to production
- Reproducibility, versioning and the cost of manual ML
- The modern MLOps toolchain at a glance
- Containerizing models with Docker
- Exposing models as REST APIs
- Batch vs. real-time serving patterns
- Kubernetes fundamentals for ML workloads
- Autoscaling and resource management
- Rolling updates and safe rollbacks
- Automated build, test and deployment pipelines
- Model validation gates before release
- Continuous delivery of models
- Tracking experiments with MLflow
- Model registry and stage promotion
- Comparing and reproducing runs
- Monitoring performance and data/concept drift
- Alerting and automated retraining triggers
- Capstone: deploy and monitor a production model
Frequently asked questions
Do I need machine-learning experience first?
Yes — CMOE focuses on deploying and operating models, so you should already be comfortable training a basic ML model. If you're newer, our data-science programs build that foundation first.
Which tools will I use?
You work hands-on with Docker, Kubernetes, CI/CD pipelines and MLflow — the standard modern MLOps stack used by production teams.
What will I be able to do afterwards?
Package, deploy, scale and monitor ML models as reliable production services, with automated delivery and drift monitoring in place.
How much does the program cost?
We quote on a call rather than publishing a figure, because the price depends on the format you pick — live online, onsite, or a private cohort for a team — and because we would rather check the programme is right for you before talking about money. An advisor goes through what it covers, what you will be able to do at the end, and the prerequisites, and then gives you the exact price and the payment options. It takes about twenty minutes and there is no obligation. Request it from the form on this page.
When does the next cohort start?
New cohorts open regularly, online and onsite, and we confirm dates on the same call as the price — partly because they move, and partly because the right date depends on which format suits you and whether you meet the prerequisites yet. Ask on the form and an advisor will give you the next available starts that fit your schedule.
Is the program online or onsite, and in which language?
Both — Epsilon runs live, instructor-led sessions online and onsite, plus dedicated corporate cohorts. Programs are delivered in English and Arabic, with bilingual materials and instructor support. Tell us your preference in the registration form.
What certificate will I receive?
A globally accredited certificate from Epsilon AI Learning — USA, carrying a unique Certificate ID and Epsilon ID. It is awarded on 80% attendance, an 80% final exam, and a completed capstone project, and it is verifiable online.
Continue your pathway
This program is part of the Epsilon certification framework. Explore the full seven-level pathway and top-up programs to build on what you learn here.
Data Scientist / MLOps
- Certified Data Scientist Professional
- CDSP Applied Professional Training Program
- Certified Data Scientist Expert (Advanced)
- Certified MLOps Engineer
After 3 end-to-end ML projects
Led by Epsilon's expert instructors
Every program is delivered by practitioners who ship AI and analytics in industry — the same team across all Epsilon programs.
Where our graduates work
A sample of the employers hiring Epsilon Learning graduates across the region and beyond.
Earning your accredited certificate
To receive the accredited certificate you need at least 80% attendance, at least 80% in the final exam, and a completed capstone project.
When the next cohort starts
Dates are confirmed on the same call as the price, because they move and because the right start depends on the format that suits you. Ask to be told when the next one opens and an advisor will come back with the starts that fit your schedule.
Tell me when the next one opens
Your name and a way to reach you. No newsletter — we write when there is a date.
Register — Certified MLOps Engineer
Tell us a little about you and we'll confirm your seat, schedule, and delivery mode.