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Reseña del curso Generative AI for Cloud Engineers de Edcorner Learning

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1000+ Prompts for Mastering Generative AI in Cloud Engineering

Formato de aprendizaje Online Course

Subcategoría Generative AI

Precio del curso $19.99

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Sobre Edcorner Learning

1000+ Prompts for Mastering Generative AI in Cloud Engineering

¿Quién es Edcorner Learning?

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Total de estudiantes

5,900 students

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Idioma del curso

English

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¿Qué se aprende en el curso de Edcorner Learning?

Understand the fundamentals, capabilities, and limitations of Generative AI in the context of cloud computing

Gain access to 1000+ prompts specifically tailored for cloud automation, cost management, security, and troubleshooting

Analyze the evolution of AI in cloud environments and how it is reshaping traditional automation workflows

Distinguish between conventional scripting/automation and GenAI-driven infrastructure generation

Evaluate and integrate leading GenAI platforms (OpenAI, Anthropic, AWS Bedrock, Google Vertex AI, Azure OpenAI) into real-world cloud operations

Learn how to authenticate, consume, and manage Generative AI APIs across multiple providers with best practices

Compare LLMs and diffusion models and their application in cloud tasks like provisioning, documentation, and monitoring

Engineer effective prompts for generating Infrastructure-as-Code (IaC) using Terraform, CloudFormation, and Pulumi

Automatically generate Kubernetes YAMLs, Helm Charts, and CI/CD pipeline code using GenAI tools

Use GenAI for VM right-sizing, resource planning, and predictive scaling to optimize cost and performance

Detect anomalies, summarize logs and metrics, and generate RCA documents and incident reports using natural language prompts

Implement GenAI-driven threat detection, IAM policy generation, and audit log analysis

Secure your GenAI usage through best practices including prompt injection prevention, encryption, and key rotation

Create GitOps and DevOps workflows powered by LLMs, including deployment scripts and rollback logic

Build self-healing cloud environments with prompt-driven agents and LLM-integrated monitoring tools

Use GenAI to auto-generate serverless functions, microservices skeletons, and API documentation

Integrate Generative AI into CI/CD systems (GitHub Actions, GitLab CI, Jenkins) for automation and validation

Develop AI-powered ChatOps assistants for Slack or Teams to manage cloud resources using natural language

Conduct hands-on labs to build real-world projects using GenAI across AWS, Azure, and GCP environments

Become capable of leading GenAI initiatives in cloud engineering, platform automation, and cloud-native DevOps transformation

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