Learning Paths for Technical Professionals
AI for DevOps Engineers
This starter learning path introduces DevOps engineers to generative AI fundamentals and practical applications, focusing on tools like GitHub Copilot and Amazon Q Developer. Learners explore GenAI concepts, prompt engineering, hands-on model deployment, and integration of AI into DevOps workflows, including infrastructure as code and cloud automation.
Learning objectives:
- Explain core generative AI concepts, including models, tokens, embeddings, and their relevance to DevOps and DevSecOps.
- Apply prompt engineering strategies to optimize GenAI tools for automating DevOps and DevSecOps tasks.
- Deploy and run generative AI models locally, including setting up environments and implementing case studies like PersonalGPT.
- Utilize GitHub Copilot for code generation, workflow automation, and DevOps-specific use cases, understanding its subscription models and features.
- Integrate Amazon Q Developer into DevOps pipelines for coding, infrastructure as code (Terraform), AWS automation, and handling external packages.
Target audience:
This path is designed for DevOps and DevSecOps engineers, programmers, and IT professionals seeking to leverage generative AI in their workflows. It is suitable for those new to GenAI as well as practitioners looking to integrate tools like GitHub Copilot and Amazon Q Developer into DevOps automation and cloud operations.