ML Software Engineering

by We Cloud Data Claim Listing

This module teaches students the necessary software engineering skills for model deployment. Students will learn the basics of web applications, REST APIs, model serving, and inference.

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Course Details

This module teaches students the necessary software engineering skills for model deployment. Students will learn the basics of web applications, REST APIs, model serving, and inference.

Students will not only learn how to create inference APIs but also how to deploy the prediction services in a local Docker container, AWS Lambda, Sagemaker, and AWS ECS/Fargate. The scaling part will be introduced in a later module.

 

Learning Outcomes

  • Learn the fundamentals of web applications and Microservices

  • Learn how to build and deploy basic Python-based applications using FastAPI and Flask

  • Learn how to create an inference API using FastAPI

  • Learn how to package and structure ML projects

  • Learn how to deploy ML Models in different types of infrastructures

 

Key Skill:

Model Serving, Prediction Service, Inference API, Model Deployment

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