What will you learn in DevOps and AI on AWS Specialization course
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Understand how DevOps principles integrate with AI and machine learning workflows on AWS.
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Learn how to design, build, and deploy AI-powered applications using AWS services.
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Implement CI/CD pipelines for ML and AI projects.
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Work with infrastructure as code (IaC) and automation tools in cloud environments.
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Monitor, secure, and optimize AI applications in production.
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Gain practical exposure to AWS-native DevOps and AI services.
Program Overview
Foundations of DevOps on AWS
⏳ 3–4 weeks
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Learn DevOps principles: collaboration, automation, CI/CD, and monitoring.
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Understand AWS core services (EC2, S3, IAM, CloudWatch).
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Explore infrastructure as code concepts using AWS tools.
AI and Machine Learning on AWS
⏳ 4–5 weeks
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Learn how AWS supports AI/ML development and deployment.
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Explore services such as Amazon SageMaker conceptually.
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Understand data preparation, model training, and deployment workflows.
CI/CD for AI and ML Workloads
⏳ 3–4 weeks
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Build CI/CD pipelines for machine learning applications.
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Automate model testing, deployment, and monitoring.
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Learn MLOps concepts within AWS ecosystems.
Monitoring, Security, and Optimization
⏳ 3–4 weeks
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Monitor AI applications using AWS tools.
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Apply security best practices for cloud-based ML systems.
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Optimize cost, performance, and scalability in AI-driven systems.
Get certificate
Job Outlook
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Highly valuable for DevOps Engineers, Cloud Engineers, and ML Engineers.
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Strong demand for professionals with MLOps and AWS expertise.
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Relevant for roles such as Cloud DevOps Engineer, MLOps Engineer, and AI Infrastructure Engineer.
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Supports AWS certification pathways and advanced cloud career tracks.
