Source: https://www.udemy.com/course/generative-and-agentic-ai-in-production/What you’ll learn
- Deploy OpenAI LLM apps to production on Vercel, AWS, Azure, and GCP.
- Design SaaS architectures with IAM, EC2, S3, CloudFront, Lambda, Route 53, ECS, and App Runner.
- Build AI platforms on AWS Bedrock and SageMaker with secure API Gateway endpoints.
- Automate infrastructure with Terraform and ship continuously via GitHub Actions.
- Implement multi-cloud AI engineering, including Azure and GCP deployments.
Requirements
- While it’s ideal if you can code in Python and have some experience working with LLMs, this course is designed for a very wide audience, regardless of background. I’ve included a whole folder of self-study labs that cover foundational technical and programming skills. If you’re new to coding, there’s only one requirement: plenty of patience!
- The course runs best if you have a small budget for APIs, but it’s totally your choice. You can complete the entire course with no API spend. If you do wish to use frontier models, the typical spend would be under $5. You can choose to access more capabilities if you’re comfortable spending a little more.
Download Links
Password: cms.ddpanda.org
