Enroll Course: https://www.udemy.com/course/devops-to-mlops-bootcamp/
The world of technology is constantly evolving, and the intersection of DevOps and Machine Learning, known as MLOps, is no exception. For DevOps engineers and infrastructure professionals looking to stay ahead of the curve, transitioning into MLOps is a smart career move. The ‘Ultimate DevOps to MLOps Bootcamp – Build ML CI/CD Pipelines’ on Udemy offers a comprehensive and hands-on approach to making this transition.
This bootcamp is meticulously crafted to guide you through the entire lifecycle of a machine learning project, from initial data processing to production deployment. The course utilizes a practical, real-world house price prediction use case, making the learning process tangible and relatable. You’ll begin by setting up your development environment with essential tools like Docker and MLFlow for robust experiment tracking. Understanding the machine learning lifecycle is a core component, and the course provides ample hands-on experience with crucial aspects like data engineering, feature engineering, and model experimentation, all within the familiar Jupyter notebook environment.
The journey continues with packaging your trained model using FastAPI and creating an intuitive Streamlit-based UI for interaction. A significant focus is placed on automation, with the course detailing how to leverage GitHub Actions workflows for CI/CD pipelines and utilizing DockerHub for efficient model container management. This ensures your ML models can be built, tested, and deployed with streamlined efficiency.
Moving into more advanced territory, the bootcamp delves into building scalable inference infrastructure on Kubernetes. You’ll learn to expose services, manage service discovery, and understand production-grade model serving with Seldon Core. Monitoring is paramount in production, and the course covers this extensively, guiding you through setting up Prometheus and Grafana dashboards for comprehensive deployment monitoring.
To cap it all off, the course introduces GitOps principles with ArgoCD, providing a clean and automated method for managing and deploying changes to your Kubernetes cluster. This holistic approach ensures you’re not just learning individual tools, but how they integrate seamlessly into a production-ready MLOps workflow.
By the end of this bootcamp, you will possess the practical skills and theoretical knowledge necessary to operate and automate machine learning workflows using DevOps best practices. This makes the ‘Ultimate DevOps to MLOps Bootcamp’ an invaluable resource for anyone aspiring to excel in MLOps or AI Platform Engineering roles.
Enroll Course: https://www.udemy.com/course/devops-to-mlops-bootcamp/