Description:

The mlops course covers the fundamentals of Machine Learning Operations (MLOps), focusing on how to deploy, manage, and scale machine learning models effectively in production environments. You will learn industry best practices for streamlining the machine learning workflow, ensuring model reproducibility, and optimizing model performance through continuous integration and deployment.

Key Highlights:

• MLOps Fundamentals
• Model Deployment Strategies
• Continuous Integration for ML
• Model Monitoring and Scalability

What you will learn:

• Understanding MLOps Principles
  Learn the core concepts of MLOps and how it integrates machine learning with operations for efficient model deployment.
• Deployment Strategies
  Explore various deployment strategies such as continuous deployment, A/B testing, and canary releases for ML models.
• Continuous Integration for ML
  Implement CI/CD pipelines for machine learning projects to automate testing, packaging, and deployment processes.
• Model Monitoring and Scalability
  Monitor model performance, detect drift, and scale machine learning models to meet changing business requirements.