The fusion of Machine Learning (ML) and DevOps has given rise to one of the most in-demand fields in modern technology—MLOps (Machine Learning Operations). As businesses adopt AI-driven systems, the need for experts who can deploy, monitor, and manage machine learning models efficiently is skyrocketing. To address this growing demand, DevOpsSchool offers a comprehensive MLOps Certified Professional Course—a robust training program designed to help professionals become industry-ready MLOps engineers.
This course, mentored by Rajesh Kumar—a global thought leader with over 20 years of expertise in DevOps, DevSecOps, SRE, DataOps, AIOps, Kubernetes, and Cloud—brings deep hands-on exposure, real-world projects, and cutting-edge learning to help learners master the entire lifecycle of ML deployment.
What is MLOps and Why It Matters
MLOps (Machine Learning Operations) integrates ML systems into DevOps principles to ensure automation, reproducibility, and scalability in production environments. It covers the end-to-end lifecycle of machine learning pipelines, including:
- Data collection, cleaning, and transformation
- Model training, validation, and deployment
- Version control and continuous integration (CI/CD)
- Monitoring and retraining in production
With MLOps, organizations can streamline ML workflows, reduce manual operations, and bridge the gap between data science and IT operations—a skill set now critical for AI success.
Why Choose DevOpsSchool for MLOps Training
As a pioneer in DevOps and Cloud education, DevOpsSchool combines industry-aligned curriculum with real-world application. Its MLOps certification program equips participants to deploy ML systems at scale, manage model versioning, and automate workflows seamlessly across hybrid-cloud environments.
Key Advantages of DevOpsSchool’s MLOps Program
| Feature | DevOpsSchool | Others |
|---|---|---|
| Lifetime Technical & LMS Access | ✅ | ❌ |
| Real-World Projects and Labs | ✅ | ❌ |
| 250+ MLOps Interview Questions & Kits | ✅ | ❌ |
| Hands-on Cloud Labs (AWS-based) | ✅ | ❌ |
| Mock Tests and Resume Assistance | ✅ | ❌ |
| Mentor Support by Rajesh Kumar | ✅ | ❌ |
This program is carefully crafted to help engineers master concepts from theory to production deployment.
Course Structure: Build End-to-End MLOps Expertise
The MLOps Certified Professional Course offers both self-learning and live instructor-led formats, giving participants flexibility and experiential learning through hands-on projects.
Core Modules
- Introduction to MLOps
- Key principles of automation, version control, and collaboration
- Understanding MLOps lifecycle: development to deployment
- Linux for MLOps
- Master shell scripting for automation
- Build and schedule model pipelines using Cron Jobs
- AWS for MLOps
- Deploy ML models using AWS EC2, S3, SageMaker
- Secure, scalable infrastructure setup for cloud ML workflows
- Docker and Kubernetes
- Package and deploy models using Docker containers
- Automate orchestration with Kubernetes and Helm charts
- Continuous Integration & GitOps with ArgoCD
- Automate ML pipeline deployments
- Manage infrastructure with GitHub and Terraform
- Monitoring and Observability
- Implement Prometheus and Grafana for real-time insights
- Detect model drift and automate retraining pipelines
- MLflow, Kubeflow, and Airflow
- Track experiments, version models, and reproduce results
- Build end-to-end workflows for data ingestion to deployment
- API and CI/CD Integration
- Develop REST APIs using Flask and Python
- Integrate monitoring alerts and deployment triggers
- Project and Documentation Tools
- Manage workflows using Jira & Confluence
- Document the MLOps pipeline for collaborative alignment
This holistic curriculum ensures learners can build, deploy, and monitor ML models at an enterprise scale—an essential capability in today’s AI ecosystem.
Hands-On Projects and Cloud Labs
Every participant gets to work on real-world projects that simulate actual MLOps business use cases. Projects involve:
- Automating ML pipelines using ArgoCD and Airflow
- Deploying models on AWS and Kubernetes clusters
- Monitoring production systems using Prometheus and Grafana
- Handling live model retraining under evolving data conditions
The hands-on labs are hosted on DevOpsSchool’s AWS Cloud, providing a real-world enterprise environment for learners.
Learning from the Master: Rajesh Kumar
The backbone of DevOpsSchool’s success lies in its expert mentor, Rajesh Kumar—a globally renowned professional trainer and consultant. His vision for cross-functional DevOps education has empowered over 50,000 learners worldwide across domains such as:
- DevOps, DevSecOps, and SRE
- AIOps, DataOps, and MLOps
- Cloud (AWS, Azure, GCP)
- Containerization with Kubernetes and Docker
His mentor-driven training methodology focuses on hands-on practice, helping professionals translate theory into operational excellence.
Career Opportunities After MLOps Certification
MLOps professionals are now among the top 5 most sought-after roles in AI. Career paths post-certification include:
- MLOps Engineer
- Machine Learning Engineer
- AI Infrastructure Engineer
- Cloud Automation Architect
- Data Science Operations Specialist
Average salaries for MLOps Engineers in the US range between $111,000 to $147,000 annually, with rising demand across industries like finance, healthcare, and cloud computing.
Student Testimonials
Abhinav Gupta, Pune:
“The training was detailed, and Rajesh explained each MLOps concept with real project examples. Highly recommended!”
Indrayani, India:
“I gained the confidence to handle real-world model deployments using Kubernetes and MLflow. The support team was excellent.”
Sumit Kulkarni, Bangalore:
“The hand-on AWS labs made it easy to implement everything practically. Great course!”
Why DevOpsSchool is the Best Choice for MLOps Certification
Unlike generic online academies, DevOpsSchool ensures a mentor-guided, hands-on, job-oriented approach. Every course is backed by lifetime LMS access, 24/7 technical support, and career assistance.
The MLOps Certified Professional Course is more than a learning program—it’s a launchpad for higher-paying roles in AI and Cloud Engineering.
Enroll Today – Build the Future of Machine Learning Operations
Don’t just learn MLOps—master it with guidance from the best. Join the MLOps Certified Professional Program and transform your ML career with actionable, scalable skills for the real world.
Contact DevOpsSchool:
- Email: contact@DevOpsSchool.com
- Phone & WhatsApp (India): +91 99057 40781
- Phone & WhatsApp (USA): +1 (469) 756-6329