Overview
In this 5-hour course, explore the essentials of MLOps with a practical, hands-on approach to machine learning operations. You will learn about continuous integration, deployment, training, and monitoring while gaining practical experience with tools like MLflow, BentoML, Apache Kafka, and AWS SageMaker. The course also covers data preparation and security best practices.

What I will be able to do after this course
Understand the MLOps lifecycle and its significance in model deployment
Set up continuous integration, deployment, and monitoring pipelines
Manage data ingestion, cleaning, and transformation for machine learning
Leverage MLflow for experiment tracking and model versioning
Serve machine learning models in production using BentoML
Course Instructor(s)
KodeKloud, founded by Mumshad Mannambeth, is an expert-led platform in DevOps, Cloud Computing, and Automation. With a strong background at Dell EMC as a Solutions Architect, Mumshad develops industry-aligned courses to help learners thrive in tech and pass certification exams.

Who is it for?
This course is ideal for data scientists, machine learning engineers, and DevOps professionals looking to advance their MLOps knowledge. It's also perfect for professionals transitioning from software or data engineering to MLOps.