What you’ll learn
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Build end-to-end Machine Learning pipelines with MLOps best practices
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Understand and implement ML lifecycle from data engineering to model deployment
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Set up MLFlow for experiment tracking and model versioning
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Package and serve models using FastAPI and Docker
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Automate workflows using GitHub Actions for CI pipelines
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Deploy inference infrastructure on Kubernetes using KIND
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Use Streamlit for building lightweight ML web interfaces
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Learn GitOps-based CD pipelines using ArgoCD
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Serve models in production using Seldon Core
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Monitor models with Prometheus and Grafana for production insights
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Understand handoff workflows between Data Science, ML Engineering, and DevOps
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Build foundational skills to transition from DevOps to MLOps roles
How to Enroll DevOps to MLOps Bootcamp: Build & Deploy MLSystems End-2-End course?
How many members can access this course with a coupon?
DevOps to MLOps Bootcamp: Build & Deploy MLSystems End-2-End Course coupon is limited to the first 1,000 enrollments. Click 'Enroll Now' to secure your spot and dive into this course on Udemy before it reaches its enrollment limits!
