In today’s data-driven world, Machine Learning (ML) is transforming industries across healthcare, finance, e-commerce, and technology. However, building ML models is only part of the equation — deploying, monitoring, and scaling these models efficiently is equally critical. This is where MLOps (Machine Learning Operations) comes in, combining DevOps principles with ML lifecycle management to ensure reliable, scalable, and reproducible ML deployments.
To gain in-depth expertise in this emerging domain, the MLOps Certified Professional Course by DevOpsSchool is designed to help professionals become leaders in machine learning operations, deployment, and monitoring.
Why MLOps is a Game-Changer
Traditional ML workflows often fail in production due to challenges like version control, model reproducibility, and pipeline automation. MLOps addresses these issues by integrating DevOps best practices with ML lifecycle management, enabling organizations to:
- Deploy models faster with automated pipelines
- Monitor model performance in real-time
- Ensure reproducibility across environments
- Scale ML solutions efficiently across cloud and on-premise systems
Professionals skilled in MLOps are increasingly in demand, making it a career-critical skill in AI-driven enterprises.
About the MLOps Certified Professional Course
The MLOps Certified Professional Program by DevOpsSchool offers comprehensive, hands-on training for professionals aiming to master ML deployment, automation, and lifecycle management.
The course is guided by Rajesh Kumar, a globally recognized trainer in DevOps, MLOps, Cloud, and DataOps with over 20 years of experience. Under his mentorship, learners gain real-world exposure to MLOps tools, pipeline automation, CI/CD integration for ML, and monitoring frameworks.
Learn more about him at RajeshKumar.xyz.
Course Highlights
- Full coverage of MLOps principles and best practices
- Hands-on labs for model deployment, CI/CD pipelines, and monitoring
- Integration with Kubernetes, Docker, and Cloud platforms
- Exposure to tools like MLflow, Kubeflow, Airflow, and Seldon Core
- Guidance on MLOps certification and career development
Course Overview: MLOps Certified Professional
| Feature | Details |
|---|---|
| Course Title | MLOps Certified Professional |
| Trainer | Rajesh Kumar – 20+ years in DevOps, Cloud & AI/ML |
| Duration | 30–40 Hours (Instructor-led Live Training) |
| Mode | Online / Classroom / Corporate |
| Certification | MLOps Certified Professional from DevOpsSchool |
| Tools Covered | MLflow, Kubeflow, Airflow, Docker, Kubernetes, Seldon Core |
| Project Work | Real-time MLOps pipelines and deployment projects |
Who Should Enroll
The program is suitable for professionals from diverse backgrounds:
- Data Scientists looking to deploy ML models efficiently
- DevOps Engineers integrating ML into CI/CD pipelines
- AI/ML Engineers aiming to scale ML solutions
- Software Developers transitioning into AI operations
- Cloud Architects managing ML workloads on cloud platforms
Learning Outcomes
After completing the course, participants will be able to:
- Build and manage end-to-end ML pipelines
- Implement CI/CD for ML models using industry tools
- Monitor and maintain model performance in production
- Ensure reproducibility and version control for ML workflows
- Deploy ML models on cloud and Kubernetes environments
- Optimize ML lifecycle management with automation and orchestration
Course Curriculum
Module 1: Introduction to MLOps
- Importance of MLOps in modern AI workflows
- Challenges in traditional ML deployment
- Overview of tools and platforms
Module 2: ML Lifecycle & Pipeline Automation
- Model training, versioning, and tracking
- Data preprocessing and feature engineering pipelines
- Integration with CI/CD frameworks
Module 3: Model Deployment Strategies
- Containerization with Docker
- Deployment on Kubernetes clusters
- Serverless and cloud-native deployment options
Module 4: Monitoring & Maintenance
- Performance tracking with MLflow and Prometheus
- Automated retraining pipelines
- Alerting and logging for production ML models
Module 5: Security & Governance in MLOps
- Role-based access control for ML pipelines
- Compliance and reproducibility best practices
- Securing data and model artifacts
Module 6: Capstone Projects
- Building end-to-end MLOps pipelines
- Real-world case studies integrating multiple tools
- Hands-on deployment and monitoring exercises
Why Choose DevOpsSchool for MLOps Training
DevOpsSchool is globally recognized for delivering practical, instructor-led training in DevOps, Cloud, and AI/ML domains. The platform emphasizes hands-on, project-driven learning, preparing learners for real-world challenges.
Key Advantages:
- Mentorship by Rajesh Kumar, an industry leader in DevOps and MLOps
- Hands-on labs and real-world projects for practical experience
- Flexible training options: online, self-paced, and corporate programs
- Lifetime access to course materials and global professional community
- Assistance with MLOps certification and career guidance
Career Opportunities After MLOps Certification
MLOps professionals are in high demand as enterprises scale AI initiatives. Certification in MLOps opens doors to roles such as:
- MLOps Engineer
- AI/ML Engineer
- DevOps Specialist for ML pipelines
- Cloud AI Architect
- DataOps Engineer
Average Salary Insights:
- India: ₹12 LPA – ₹30 LPA
- USA: $120,000 – $180,000 per annum
These roles are prevalent across tech giants, financial services, healthcare, and cloud-native startups, reflecting the high value of MLOps skills.
Conclusion
The MLOps Certified Professional Course by DevOpsSchool equips learners with end-to-end MLOps expertise, blending DevOps principles with modern ML practices.
With guidance from Rajesh Kumar, you gain the hands-on skills, strategic insights, and certification needed to excel in the growing field of AI operations.
Whether your goal is to deploy scalable ML solutions, automate workflows, or become an MLOps leader, this course is the perfect launchpad for your career.
Contact DevOpsSchool
📧 Email: contact@DevOpsSchool.com
📞 Phone & WhatsApp (India): +91 7004215841
📞 Phone & WhatsApp (USA): +1 (469) 756-6329
🌐 Website: www.DevOpsSchool.com