Courses Details and Modules
Why Serverless ML?
You should not need to be an expert in Kubernetes or cloud computing to build an end-to-end service that makes intelligent decisions with the help of a ML model. Serverless ML makes it easy to build a system that uses ML models to make predictions. You do not need to install, upgrade, or operate any systems. You only need to be able to write Python programs that can be scheduled to run as pipelines. The features and models your pipelines produce are managed by a serverless feature store / model registry. We will also show you how to build a UI for your prediction service by writing Python and some HTML.
Module 00 (Optional)
Introductions, requirements & Machine Learning 101
Starting Date: Self Paced.
- Lecture 0 - Why Serverless ML? link
- Lecture 0 - Introduction to the course link
- What we cover - what we don’t cover
- Lecture 0 - Development Environment & Platforms link
- Lecture 0 - Introduction to Machine Learning (ML 101) link
How to write Pipelines in Python and run your first Prediction Service
Starting Date: Tuesday 27th September 2022 - 5PM CET
- Feature Engineering in Pandas
- Iris as a Prediction Service
- Refactor notebooks into Python modules/functions and Notebooks
Data modeling and the Feature Store. The Credit-card fraud prediction service.
- Data modeling and the Data Warehouse / Feature Store
- Feature Pipelines with synthetic data
Training Pipelines, Inference Pipelines, and the Model Registry.
Release Date: 11th Oct 2022
- Feature store Transformations vs Scikit-Learn Transformations
Serverless User Interfaces for Machine Learning Systems.
Release Date: 24th Oct 2022
- Effective Stakeholder Communication
- Interactive User Interfaces
MLOps Principles: Automated Testing, Versioning, Upgrades/Rollback
- Developing new versions of a feature and a model
- Feature Logic tests: Pytest for Python functions outside notebooks
- End-to-End tests with sample data
- Data Quality tests with Great Expectations
Real-time Machine Learning Systems
Release Date: 22 Dec 2022
- Online Inference Pipelines