DevOps + AI (MLOps)

About DevOps + AI (MLOps)

DevOps + AI, commonly referred to as MLOps (Machine Learning Operations), focuses on streamlining the deployment, automation, and management of AI/ML models in production environments using DevOps principles and tools. This course provides in-depth training on how to operationalize machine learning workflows, manage model lifecycles, and ensure reproducibility, scalability, and monitoring of AI systems. Learners will gain hands-on experience integrating CI/CD pipelines with ML frameworks, automating retraining and deployment processes, and applying version control to datasets and models. Designed for ML engineers, DevOps professionals, and data scientists, this course bridges the gap between data science and production-grade infrastructure. By the end of the course, students will be able to build, deploy, monitor, and scale AI solutions in a DevOps-driven environment.

DevOps + AI (MLOps) Course Objectives

You will be expertise and eligible for:

• Automate the ML lifecycle with CI/CD tools like GitHub Actions, Jenkins, and Azure DevOps
• Deploy machine learning models using Docker and Kubernetes
• Implement model versioning and tracking with MLflow and DVC
• Set up continuous training pipelines for data drift and model retraining
• Monitor model performance and system health in production environments
• Collaborate efficiently between data science and engineering teams using MLOps best practices

Pre-Requisites

The course is suitable for AI/ML professionals, DevOps engineers, and cloud developers with:

• Basic knowledge of machine learning and Python
• Familiarity with DevOps tools like Git, Docker, or CI/CD pipelines
• Understanding of cloud platforms such as Azure, AWS, or GCP (preferred)

Duration of the Course

• "L" understands the challenges like security, time limitations, and location that prevent many learners from attending traditional classes.
• Duration of 50 sessions.
• 1 hour per day.
• Provides soft copy of every class after its completion.
• Provides class recording sessions.