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DevOps to MLOps: Unlock the Future of AI and Cloud Careers

Posted By: lucky_aut
DevOps to MLOps: Unlock the Future of AI and Cloud Careers

DevOps to MLOps: Unlock the Future of AI and Cloud Careers
Published 3/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 44m | Size: 900 MB

Master the transition from DevOps to MLOps with hands-on labs in Kubernetes, Terraform, CI/CD, and AI model deployment.

What you'll learn
Understand the key concepts and benefits of MLOps in DevOps workflows.
Learn how to integrate machine learning models into CI/CD pipelines.
Gain hands-on experience deploying MLOps solutions using cloud platforms.
Master the tools and technologies required to transition from DevOps to MLOps.

Requirements
Basic understanding of DevOps concepts and practices.
Familiarity with cloud platforms (AWS, GCP, or Azure) is beneficial but not required.
No prior experience in machine learning is needed; you will learn from scratch.

Description
Are you a DevOps Engineer, Cloud Professional, or AI Enthusiast looking to transition into the high-demand field of MLOps? This course is designed to help you bridge the gap between DevOps and AI Operations (AIOps) by equipping you with practical skills and real-world use cases.In this course, you will:Understand the evolution from DevOps to MLOps and why AI-driven workflows are the future.Learn Kubernetes, Terraform, and CI/CD pipelines tailored for AI/ML model deployment.Implement real-world projects on AWS, Azure, and GCP using Dockerized ML models.Master end-to-end automation of Machine Learning pipelines with GitOps, ArgoCD, and Kubeflow.Deploy AI models efficiently using feature stores, model registries, and cloud-native monitoring.Who is this course for?DevOps and Cloud Engineers looking to pivot into MLOps & AI OperationsSoftware Engineers eager to automate Machine Learning pipelinesData Scientists interested in productionizing AI modelsAI & ML professionals who want to scale deployments with Kubernetes and TerraformWhat makes this course unique?100% Hands-on Labs with real-world MLOps projectsIndustry Best Practices from top tech companiesCI/CD Pipelines for AI/ML models using Terraform, Kubernetes, and Cloud servicesIntegrations with AWS SageMaker, Azure ML, and GCP AIJoin now and unlock the future of DevOps & MLOps careers!

Who this course is for
DevOps engineers looking to transition into MLOps.
Cloud professionals interested in adding machine learning to their DevOps workflows.
AI enthusiasts who want to understand how MLOps bridges AI and DevOps.
Engineers or developers aiming to enhance their careers with in-demand MLOps skills.