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MLOps Certification Training
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About Course
🌐 MLOps Online Training
MLOps (Machine Learning Operations) is a modern practice that combines machine learning, DevOps, and data engineering to automate and manage the end-to-end lifecycle of ML models. It is widely used by organizations to build scalable, reliable, and production-ready AI systems. MLOps ensures smooth collaboration between data scientists and operations teams while maintaining model performance in real-time environments.
This course provides in-depth, hands-on experience in building ML pipelines, automating workflows, deploying models, and monitoring performance using industry-standard tools and real-time projects.
🚀 Its Core Capabilities Include:
ML Pipeline Automation:
Automate data processing, model training, and deployment workflows.
Model Deployment:
Deploy ML models as APIs or real-time services.
CI/CD for ML:
Implement continuous integration and delivery for ML pipelines.
Model Monitoring:
Track performance, detect drift, and retrain models.
Version Control:
Manage code, data, and model versions efficiently.
Containerization:
Use Docker and Kubernetes for scalable deployment.
Collaboration:
Enable teamwork between data scientists and DevOps engineers.
📍 Bonus: Certification Tracks
- DevOps Associate Certification
- MLOps Developer Certification
- MLOps Application Developer Certification
- MLOps Expert Certification (Viswa Online Trainings)
MLOps Training Course Syllabus
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MLOps Course Key Features
- Live Instructor based training with software
- Certification Oriented content
- Hands-on complete Realtime training
- Flexible schedule demo's & classes
- Live recorded videos access
- Study material provided
- JOB Assistance
Course completion certificate
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CHOOSE YOUR OWN COMFORTABLE LEARNING EXPERIENCE
Live Virtual Training
- Schedule your sessions at your comfortable with timings
- Instructor-Led training real time projects
- Certification Guidance
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Self-Paced Learning
- Complete set of live-online training session recorded videos.
- Learn technology at your own pace.
- Get access for lifetime.
Corporate Training
- Learn as a full day schedule with discussions, exercises.
- Practical use cases.
- Design your own syllabus based
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MLOps Online Training FAQ'S
What is MLOps?
MLOps (Machine Learning Operations) is a set of practices that combines machine learning, DevOps, and data engineering to manage the ML lifecycle. It ensures models are developed, deployed, monitored, and maintained efficiently in production.
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Why is MLOps important in machine learning projects?
- MLOps helps automate the ML pipeline and ensures consistency between development and production environments. It improves collaboration, scalability, and reliability of machine learning systems.
What are the key components of an MLOps pipeline?
- An MLOps pipeline includes data collection, data preprocessing, model training, validation, deployment, and monitoring. Each stage is automated and integrated to ensure continuous delivery of ML models.
What is model deployment in MLOps?
- Model deployment is the process of making a trained ML model available for use in real-world applications. It can be deployed as APIs, batch jobs, or real-time services depending on the use case.
What is model monitoring in MLOps?
Model monitoring tracks model performance in production to detect issues like data drift or performance degradation. It ensures the model continues to provide accurate predictions over time.
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