The rise of Artificial Intelligence (AI) and Machine Learning (ML) has changed the landscape of modern technology—but with these innovations comes a challenge: operationalizing machine learning models at scale. This is where MLOps (Machine Learning Operations) steps in to bridge the gap between data science and operations. The MLOps Certified Professional Course offered by DevOpsSchool empowers professionals to master this intersection of ML, DevOps, and automation—making them invaluable in industries driven by intelligent data solutions.
Led by Rajesh Kumar, a globally recognized expert in DevOps, MLOps, SRE, and Cloud Technologies (https://www.rajeshkumar.xyz/), this course offers an unmatched learning experience designed to prepare both beginners and experienced engineers to handle real-world MLOps challenges confidently and effectively.
Understanding MLOps: The Backbone of Scalable AI
MLOps, short for Machine Learning Operations, combines machine learning, software engineering, and DevOps practices to manage the end-to-end ML lifecycle—from data processing to deployment and continuous monitoring.
In today’s fast-paced environments, companies need efficient pipelines to train, deploy, and monitor models seamlessly. MLOps ensures:
- Automated workflows from model training to production deployment
- Version control for datasets and models
- Real-time monitoring for drift detection and performance metrics
- Collaboration between data scientists, ML engineers, and DevOps teams
Simply put, MLOps enables stable, scalable, and reliable AI implementation in production systems.
About DevOpsSchool’s MLOps Certified Professional Course
The MLOps Certified Professional program by DevOpsSchool is tailored for modern professionals aiming to excel in machine learning deployment, scalability, and automation. Designed with a blend of theoretical grounding and real-world case studies, it caters to analysts, AI developers, cloud professionals, and DevOps engineers.
Program Highlights
| Feature | DevOpsSchool MLOps Certified Professional |
|---|---|
| Duration | 35 Hours (Live, One-to-One, or Corporate Formats) |
| Delivery Mode | Online (Instructor-led on GoToMeeting) |
| Trainer | Rajesh Kumar – 20+ Years of Experience |
| Certification | DevOps Certified Professional (Accredited by DevOpsCertification.co) |
| Support | Lifetime LMS Access and 24×7 Technical Support |
| Real-Time Labs | Kubernetes, Docker, Jenkins, MLflow, ArgoCD, AWS |
| Assessment | Hands-On Projects, Assignments, and Evaluation Tests |
| Job Assistance | Interview Kits, Mock Sessions, Resume Support |
The course curriculum aligns perfectly with job requirements analyzed from thousands of global AI and MLOps roles.
Detailed Curriculum Overview
DevOpsSchool’s MLOps course is divided into hands-on modules focusing on automation, scalability, monitoring, and cross-team collaboration.
1. Introduction to MLOps
- What is MLOps and why it matters
- MLOps lifecycle overview: development to monitoring
- Principles of automation, scalability, and collaboration
2. MLOps Tools and Technologies
- Docker & Kubernetes: Containerization and orchestration for ML models
- Jenkins & ArgoCD: CI/CD automation for ML pipelines
- MLflow & Kubeflow: Experiment tracking and model versioning
- Prometheus & Grafana: Model performance monitoring and visualization
3. Cloud and Infrastructure Mastery
- Deploying models using AWS (EC2, Lambda, SageMaker)
- Managing ML infrastructure with Terraform (IaC)
- Building scalable and fault-tolerant systems
4. Data and Model Management
- Data validation, cleaning, and transformation
- Experiment tracking in MLflow and Kubeflow Pipelines
- Managing model drift and updates using CI/CD principles
5. Monitoring and Governance
- Automating model retraining pipelines
- Monitoring performance metrics in Prometheus and Grafana dashboards
- Implementing audit trails and governance for MLOps compliance
Through this structured learning, students develop the ability to translate machine learning prototypes into production-ready architectures with reliable monitoring controls.
What Makes DevOpsSchool’s MLOps Course Stand Out?
While several MLOps certifications exist, DevOpsSchool’s program outshines others due to its focus on real-world application, expert mentorship, and global industry recognition.
| Feature | DevOpsSchool | Other Providers |
|---|---|---|
| Trainer Expertise | Led by Rajesh Kumar, 20+ yrs exp. | Mixed or non-specialist trainers |
| Real-Time Projects | Yes, with guided implementation | Often limited or simulated tasks |
| Lifetime Technical Support | Included | Usually time-limited |
| Interview Preparation Kit | Provided | Not always available |
| Cross-Tool Mastery (Docker, MLflow, ArgoCD, Terraform) | Included | Partial |
| Global Recognition | Verified by DevOpsCertification.co | Varies |
DevOpsSchool’s approach focuses on practice-based learning, ensuring participants can automate an entire ML pipeline independently after completion.
Career Benefits and Potential Roles
MLOps professionals are among the most sought-after experts in the AI industry because they ensure smooth integration between data science models and operational infrastructure. Completing this certification prepares you for roles such as:
- MLOps Engineer
- Machine Learning Engineer
- DataOps Engineer
- AI Infrastructure Lead
- Cloud ML Architect
Career Growth and Salary Insights
| Role | Average Annual Salary (India) | Average Annual Salary (Global) |
|---|---|---|
| MLOps Engineer | ₹12–20 LPA | $120,000–$150,000 |
| Machine Learning Engineer | ₹10–18 LPA | $115,000–$140,000 |
| AI/ML Infrastructure Specialist | ₹14–22 LPA | $130,000–$160,000 |
The demand for these professionals has grown significantly due to the rise of AI-driven enterprises and widespread cloud adoption.
Learning Experience and Student Reviews
Past participants have consistently praised Rajesh Kumar’s clarity, practical guidance, and personalized mentoring. Testimonials highlight DevOpsSchool’s engaging teaching style and result-oriented environment.
- “The MLOps training was hands-on and incredibly insightful. Rajesh made complex topics easy to grasp.” — Abhinav Gupta, Pune
- “Rajesh’s mentoring style and live project discussions gave me confidence for real-world implementation.” — Indrayani, India
- “From Docker to Kubeflow, every topic was detailed and practical. Highly recommended for DevOps professionals.” — Sumit Kulkarni, Software Engineer
Average rating: 5.0/5, based on multiple success stories and participant reviews.
How to Enroll
Ready to become an MLOps Certified Professional and accelerate your AI career? Enrollment is open for upcoming batches starting the first week of every month. Seats are limited to maintain session quality.
Contact DevOpsSchool Today:
- Email: contact@DevOpsSchool.com
- Phone & WhatsApp (India): +91 99057 40781
- Phone & WhatsApp (USA): +1 (469) 756-6329
For complete details, visit the official program page – MLOps Certified Professional Course.
Conclusion: Transform Your ML Career with DevOpsSchool
The MLOps Certified Professional program by DevOpsSchool is more than a course—it’s a career catalyst. Whether you are a developer, data scientist, or cloud architect, mastering MLOps will help you align innovation with execution. Supported by Rajesh Kumar’s world-class mentorship, hands-on projects, and lifelong learning access, you’ll be fully prepared to design, deploy, and maintain enterprise-level AI systems.
Start your journey toward becoming an industry-ready MLOps expert with DevOpsSchool today!