Learn ML deployment using FastAPI, Docker, CI/CD, and Cloud platforms
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The path covers the full lifecycle from creating FastAPI endpoints and Streamlit frontends to implementing unit tests and setting up GitHub Actions for CI/CD.
Instruction includes deploying containerized applications to both Heroku and Microsoft Azure.
One signal suggests that dense theoretical explanations could be better supported by more images to aid comprehension of difficult concepts.
The curriculum aligns with the goals of aspiring data scientists and developers through its focus on deployment tools.
