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: 

• Wrap it up in a REST API using FastAPI 

• Containerise it using Docker 

• Deploy it as a cloud-native service 

• 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. 

• They will gain an understanding of what containerisation is and get practical experience containerising a Python ASGI web application.  

• They will get practical experience setting up continuous integration & deployment pipelines using GitHub Actions. 

• 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.