Introduction: Why MLOps Is the Next Big Leap in AI
Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized how businesses operate. However, the real challenge lies not in building ML models—but in deploying, managing, and scaling them efficiently.
This is where MLOps (Machine Learning Operations) steps in, bridging the gap between data science and DevOps to create seamless, automated ML lifecycles.
If you’re looking to upskill or switch to one of the fastest-growing tech domains, the MLOps Certified Professional Course by DevOpsSchool is the perfect opportunity.
Led by Rajesh Kumar\, a global DevOps and MLOps mentor with over 20 years of experience, this program empowers you to take AI models from experimentation to large-scale production environments—confidently and efficiently.
What Exactly Is MLOps?
MLOps is the integration of Machine Learning (ML) and DevOps principles. It aims to automate and streamline the entire ML lifecycle — from data preparation, model development, and testing, to deployment, monitoring, and retraining.
Key Goals of MLOps
- Ensure reproducibility and traceability of ML experiments
- Enable continuous integration and delivery (CI/CD) for ML pipelines
- Automate model deployment and versioning
- Establish monitoring and governance for production ML systems
MLOps vs Traditional ML
| Feature | Traditional ML Workflow | MLOps-Enabled Workflow |
|---|---|---|
| Deployment | Manual and time-consuming | Automated and repeatable |
| Collaboration | Data teams work in silos | Unified DevOps & DataOps collaboration |
| Scalability | Limited scalability | Cloud-native scaling and orchestration |
| Monitoring | Minimal oversight | Continuous monitoring and model retraining |
| Reproducibility | Hard to track models | Version-controlled pipelines |
In short, MLOps is the DevOps for AI systems, ensuring ML models perform reliably in real-world, large-scale environments.
About DevOpsSchool – Building Global Tech Leaders
DevOpsSchool.com is a globally recognized learning platform offering professional training and certifications in DevOps, DevSecOps, SRE, DataOps, AIOps, Cloud, and MLOps.
With a strong network of trainers and mentors, DevOpsSchool has trained over 100,000 professionals worldwide through live, instructor-led, project-based programs.
Its MLOps certification course stands as a testament to DevOpsSchool’s mission—to make tech education practical, accessible, and globally respected.
Meet Your Mentor – Rajesh Kumar
Rajesh Kumar is a globally renowned DevOps and MLOps coach with 20+ years of experience in software engineering, automation, and cloud transformation.
Key Highlights
- Founder of multiple DevOps initiatives and learning platforms
- Expert in DevOps, SRE, DataOps, AIOps, Kubernetes, and MLOps
- Has trained 100,000+ professionals and 500+ corporate teams globally
- Worked with Fortune 500 companies and top-tier tech brands
Rajesh Kumar’s guidance ensures the course doesn’t just teach tools—but cultivates real-world engineering mindset and problem-solving capability essential for success in modern ML environments.
“MLOps is not just about deploying models; it’s about building intelligent systems that evolve over time.”
— Rajesh Kumar, Chief Mentor at DevOpsSchool
Inside the MLOps Certified Professional Program
Course Overview
The MLOps Certified Professional course is designed to help professionals:
- Understand the MLOps lifecycle from data collection to monitoring
- Implement CI/CD for machine learning pipelines
- Use tools like MLflow, Kubeflow, Airflow, Docker, Jenkins, and Kubernetes
- Manage models using AWS, Azure, and GCP environments
- Learn by doing—through live projects and use cases
Curriculum Breakdown
| Module | Learning Objectives |
|---|---|
| Module 1: Introduction to MLOps | Understanding architecture, principles, and real-world significance |
| Module 2: Toolchain Setup | Environment setup using Python, Docker, Kubernetes |
| Module 3: CI/CD for ML Models | Build, test, and deploy pipelines automatically |
| Module 4: MLflow and Experiment Tracking | Manage versions, track experiments, ensure reproducibility |
| Module 5: Monitoring and Governance | Detect model drift, enable auditing, ensure compliance |
| Module 6: Hands-On Projects | Work on case studies from finance, healthcare, and e-commerce |
Each module includes assignments, case studies, and practical exercises to ensure hands-on understanding.
Who Should Enroll in the MLOps Course?
The MLOps Certified Professional course is ideal for anyone interested in bridging the gap between ML model development and deployment.
Recommended for:
- DevOps Engineers expanding into AI
- Machine Learning Engineers
- Data Scientists and Analysts
- Cloud and Automation Engineers
- Software Developers exploring ML pipelines
Career Benefits of Becoming an MLOps Certified Professional
1. High Demand & Global Recognition
Enterprises worldwide are hiring MLOps engineers to streamline AI deployment.
LinkedIn listed MLOps Engineer among the Top Emerging Jobs in 2025.
2. Attractive Salary Packages
| Job Role | Average Salary (INR) | Global Average (USD) |
|---|---|---|
| MLOps Engineer | ₹10–20 LPA | $100,000 – $150,000 |
| ML Engineer | ₹9–22 LPA | $95,000 – $140,000 |
| DataOps Engineer | ₹8–18 LPA | $90,000 – $130,000 |
3. Global Opportunities
MLOps professionals are in demand across AI-driven sectors like finance, healthcare, retail, and manufacturing.
4. Real-World Skills
You’ll gain experience working on CI/CD for ML, Dockerized pipelines, cloud ML services, and real production scenarios.
Why Choose DevOpsSchool for MLOps Certification?
| Feature | Why It Matters |
|---|---|
| Mentorship by Rajesh Kumar | Learn directly from one of the world’s top DevOps experts |
| Hands-on Learning | Work on real ML pipeline projects |
| Flexible Schedules | Online live batches and weekend options |
| Globally Recognized Certificate | Validate your skills and boost your resume |
| Career Guidance | Personalized support for resume and interview preparation |
DevOpsSchool combines technical mastery with mentorship — ensuring every learner becomes industry-ready and confident in deploying production-grade ML systems.
Testimonials from Past Learners
“The MLOps course helped me automate model deployment pipelines with confidence. Rajesh’s teaching style is incredible!”
— Rohan M., MLOps Engineer
“I transitioned from DevOps to MLOps within months, thanks to the structured learning and hands-on approach.”
— Priya K., DataOps Specialist
Enroll Today & Transform Your AI Career
Don’t just build ML models—operationalize them with precision.
Join the MLOps Certified Professional Course at DevOpsSchool and become part of the global AI transformation movement.
Contact DevOpsSchool
📧 Email: contact@DevOpsSchool.com
📞 Phone & WhatsApp (India): +91 99057 40781
🌎 Phone & WhatsApp (USA): +1 (469) 756-6329
🔗 Website: www.DevOpsSchool.com
