Build job-ready skills with our Classroom and Online AI Deployment with Docker & Kubernetes Training at WebAsha Technologies. It is hands-on, practical and focused on employability.
Training Overview:
is a hands-on, job-oriented program on deploying and scaling AI and machine learning models with Docker and Kubernetes. It covers containerizing models and AI apps with Docker, building model-serving APIs, Docker Compose, Kubernetes fundamentals (pods, deployments, services), deploying models on Kubernetes, scaling and autoscaling, GPU workloads, monitoring, and CI/CD - preparing you to run AI reliably in production.
Intended Audience:
This course is ideal for ML and AI engineers, data scientists and DevOps professionals who want to deploy and scale AI and machine learning models reliably with Docker and Kubernetes.
Topics Covered:
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Docker for AI: Containerizing models.
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Model-Serving APIs: FastAPI, BentoML.
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Docker Compose: Multi-container apps.
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Kubernetes Fundamentals: Pods, deployments.
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Deploying Models on K8s: AI in production.
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Scaling: Autoscaling AI.
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GPU Workloads: Accelerated inference.
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Monitoring & CI/CD: Reliable delivery.
Requirements:
Basic computer familiarity is recommended. Online participants need a stable internet connection and a laptop/desktop for the live labs.
Pre-Requisites:
Basic Python and familiarity with machine learning help. Docker/Linux familiarity is useful; our Machine Learning and DevOps courses are good companions.
Career Benefits:
AI deployment is an essential skill. In India, MLOps and AI infrastructure engineers typically earn ₹6 LPA to ₹42+ LPA.