In today’s AI-driven world, organizations are continuously seeking ways to make machine learning (ML) models more scalable, reliable, and production-ready. That’s where MLOps (Machine Learning Operations) comes in — blending data science and DevOps principles to streamline the lifecycle of ML models from development to deployment.
If you’re looking to gain hands-on expertise and elevate your career in ML workflow automation, the MLOps Foundation Certification by DevOpsSchool is your gateway to success.
What is MLOps and Why Does It Matter?
MLOps is not just a buzzword — it’s the future of operationalizing machine learning. It aims to bridge the gap between data scientists (who build models) and operations professionals (who deploy and maintain them).
Key Benefits of MLOps Adoption:
- Automation of ML pipelines: Ensures reproducibility and efficiency in model deployment.
- Improved collaboration: Enables seamless communication between data and ops teams.
- Continuous monitoring: Detects model drift and maintains consistent performance.
- Governance and compliance: Ensures adherence to data privacy and ethical AI standards.
Organizations adopting MLOps experience better scalability, quicker model iteration, and enhanced business outcomes driven by data science.
Why Choose DevOpsSchool for MLOps Training?
DevOpsSchool stands as one of the most trusted names in DevOps and automation training globally. Its MLOps Foundation Certification Course is designed by industry experts led by Rajesh Kumar — a globally recognized DevOps and Cloud Automation mentor with over 20 years of experience across MLOps, SRE, DevSecOps, Kubernetes, and AIOps.
Highlights of the Course
- Comprehensive Curriculum: Covers MLOps fundamentals, model versioning, CI/CD automation, model monitoring, and governance.
- Hands-On Labs: Real-world projects and exercises conducted in AWS Cloud environments.
- Expert Instruction: Live instructor-led sessions with personalized mentoring from Rajesh Kumar.
- Flexible Learning: Options for self-paced study or corporate instructor-led batches.
- Post-Course Support: Lifetime LMS access, technical support, and updated materials.
Course Structure at a Glance
| Module | Description | Weightage |
|---|---|---|
| Understanding ML Lifecycle Challenges | Identifying key MLOps problems | 5% |
| Concept Discussion | Core MLOps principles | 10% |
| Demo | Guided walkthrough using tools | 25% |
| Lab & Exercises | Practical cloud-based hands-on sessions | 50% |
| Assessments & Projects | Evaluation and certification prep | 10% |
Tools & Technologies Covered
Participants work with modern toolchains widely used in MLOps pipelines:
- Docker & Kubernetes: Containerization and orchestration for ML models.
- MLflow & TensorFlow Extended (TFX): Model tracking and deployment automation.
- Terraform & Kubeflow: Infrastructure scaling and ML workflow management.
- Cloud Platforms: AWS-based environments for hands-on experimentation.
This blend of tools ensures you’re ready for real-world challenges in production-level ML implementations.
Learning Methodology
DevOpsSchool uses a balanced mix of theory and practice to build strong MLOps expertise.
Key Approaches:
- Instructor-led conceptual learning and interactive discussions.
- Detailed case studies from organizations successfully applying MLOps at scale.
- Regular quizzes and mock exams to prepare for certification.
- Direct mentor support and lifetime forum access for post-completion queries.
Career Benefits and Certification Value
The MLOps Foundation Certification differentiates you in the AI and ML industry by validating your technical competence in managing ML operations end-to-end.
Key career advantages include:
- Enhanced job roles in ML engineering and DevOps.
- Higher credibility for deploying AI-driven solutions.
- Faster promotions and cross-functional expertise recognition.
- Access to global opportunities in data automation and AI operations.
Professionals completing the course earn DevOpsSchool’s globally recognized certificate and lifetime access to proprietary materials through its LMS.
Student Feedback
DevOpsSchool has trained thousands of professionals and corporate teams worldwide. Its alumni consistently praise the MLOps certification program for its practical insights and the guidance provided by Rajesh Kumar.
Abhinav Gupta, Pune (5.0): “Highly interactive and detailed sessions — Rajesh made complex ideas easy to grasp.”
Indrayani, India (5.0): “The hands-on labs were so valuable. Great clarity and live demos!”
Ravi Daur, Noida (5.0): “Useful training for building confidence in SRE and MLOps workflows.”
Class Schedule and Global Availability
The program runs on flexible global time zones for learners across regions.
| Day | IST (India) | PST (USA) | EST (USA) | CET (Europe) | JST (Asia) |
|---|---|---|---|---|---|
| Monday–Thursday | 9:00 PM – 11:00 PM | 7:30 AM – 9:30 AM | 10:30 AM – 12:30 PM | 4:30 PM – 6:30 PM | 12:30 AM – 2:30 AM (Next Day) |
| Friday–Sunday | 9:00 AM – 11:00 AM | 7:30 PM – 9:30 PM | 10:30 PM – 12:30 AM | 4:30 AM – 6:30 AM | 1:30 PM – 3:30 PM |
Lifetime Access and Support
Each participant receives:
- Lifetime access to the LMS including recordings, notes, PDFs, and exercises.
- Interview preparation kits and topic-wise web tutorials.
- Ongoing technical support via DevOpsSchool forums (responses within 24 hours).
- Cloud lab infrastructure for AWS-powered demos and quick project setups.
Ready to Get Certified in MLOps?
The is more than just a course — it’s your roadmap to mastering end-to-end ML lifecycle management and advancing in the AI-powered industry.
To join, visit reach out at:
- Email: contact@DevOpsSchool.com
- Phone & WhatsApp (India): +91 7004215841
- Phone & WhatsApp (USA): +1 (469) 756-6329