PROJECT 01
Containerize and serve a prediction API
Example hands-on exercise
MLOPS
MLOps.
Learn how machine learning models can be deployed, monitored, and maintained in real-world workflows.
DockerCI/CDMonitoring
Bangalore, Karnataka, India · Request fees, duration & batch timings
01 / LEARNCore concepts
Understand the foundations
02 / PRACTICEApplied exercises
Work with practical examples
03 / BUILDProject ideas
Explore hands-on workflows
PROGRAM OVERVIEW
What you could learn.
A suggested progression of topics for MLOps. The final lesson plan can be confirmed with the institute before enrollment.
01From notebooks to reproducible ML pipelines
02Versioning code, datasets, and experiments
03Containerization with Docker
04Continuous integration and model delivery concepts
05Model serving and API integration
06Monitoring, drift, and iterative improvement
Recommended starting point
Working knowledge of Python and basic machine learning concepts recommended.
PRACTICAL LEARNING
Learning outcomes.
Explore the capabilities this course aims to develop.
Package an ML model for repeatable deployment
Understand model lifecycle and monitoring
Design a simple automated model delivery workflow
PORTFOLIO PRACTICE
Project ideas.
Examples of practice projects that could support the learning journey.
PROJECT 02
Create a versioned training pipeline with basic monitoring
Example hands-on exercise
LET'S CONNECT
Questions about MLOps?
Ask about fees, schedules, delivery mode, prerequisites, or course content. Our team can review your enquiry through the admin dashboard.
Your course is already selected
No payment required to enquire
Your details are stored in the institute database
Prefer WhatsApp? Chat about MLOps ↗Enquire about MLOps
Fill in your contact details to ask a question.
KEEP EXPLORING