MODEL DEPLOYMENT (2 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: LO1 – identify Characteristic of machine learning model and deployment; LO2 – describe Process of deployment workflow and pipeline; LO3 – execute Model deployment using proper mechanism; LO4 – test Machine learning model deployment solution; LO5 – Compose Correct elements of model deployment pipeline.

Topics:

1. Fundamental of Model Deployment;
2. Characterizing your Machine Learning Problem;
3. Model Deployment Tools and Set up;
4. Object Oriented Programming Part 1;
5. Object Oriented Programming Part 2;
6. Machine Learning Pipeline;
7. Deploy your First Model;
8. Deploying Machine Learning at Scale;
9. Machine Learning Deployment Using FastAPI Part 1;
10. Machine Learning Deployment Using FastAPI Part 2;
11. Testing and Securing ML Solution; Model Monitoring Part 1;
12. Model Monitoring Part 2.