AI & Machine Learning
MLOps: Machine Learning Operations
Learn to deploy, monitor, and maintain machine learning models in production.
4 Days
₹19,999
Course Overview
Building a machine learning model is only half the battle; deploying and maintaining it in a production environment is where the real challenge lies. MLOps merges Machine Learning with DevOps practices.
This course teaches you how to containerize models with Docker, track experiments, establish CI/CD pipelines for ML, and monitor models for data drift in production.
Course Curriculum
- 1Introduction to MLOps and Model Lifecycle
- 2Version Control for Data and Models (DVC)
- 3Containerization of ML Models (Docker)
- 4CI/CD Pipelines for Machine Learning
- 5Monitoring and Retraining in Production
Who Should Attend
ML Engineers, Data Scientists, DevOps Engineers
Key Information
Prerequisites:
Familiarity with Machine Learning concepts, basic Python, and some knowledge of the command line.
Exam Format:
Deploy an end-to-end ML pipeline to a cloud endpoint.
Key Benefits
- Deploy models to production
- Automate ML pipelines
- Bridge Data Science and DevOps