Course/Event Essentials
Training Content and Scope
Other Information
Aimed at Independent Users, this course will take you through the full lifecycle of “model to service”, starting off with an open-source language model and going through the steps to:
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Wrap it up in a REST API using FastAPI
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Containerise it using Docker
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Deploy it as a cloud-native service
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Continuously deploy it using GitHub Actions
Don’t worry if you haven’t used FastAPI, Docker, GitHub Actions or cloud services before – we'll learn about that as we go. It’d be helpful if you had some experience with Python, but not necessary.
Learning objectives
- Participants will gain practical experience wrapping up machine learning models as a simple REST API with FastAPI.
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They will gain an understanding of what containerisation is and get practical experience containerising a Python ASGI web application.
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They will get practical experience setting up continuous integration & deployment pipelines using GitHub Actions.
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They will get practical experience spinning up their containerised web application as a cloud-native service.
Pre-requisites
Basic level of programming. Familiarity with the Linux command-line and Python would be useful.