MLOps Zoomcamp

Objective
Teach practical aspects of productionizing ML services — from training and experimenting to model deployment and monitoring.

Target audience
Data scientists and ML engineers. Also, software engineers and data engineers interested in learning about putting ML in production.

Pre-requisites
- Python
- Docker
- Being comfortable with command line
- Prior exposure to machine learning (at work or from other courses, e.g. from ML Zoomcamp)
- Prior programming experience (at least 1+ year)

Syllabus
- Module 1: Introduction
- Module 2: Experiment tracking and model management
- Module 3: Orchestration and ML Pipelines
- Module 4: Model Deployment
- Module 5: Model Monitoring
- Module 6: Best Practices
- Project

Link: https://github.com/DataTalksClub/mlops-zoomcamp

Navigational hashtags: #armknowledgesharing #armcourses
General hashtags: #machinelearning #modeldeployment #mlops #modelmonitoring #modelorchestration

@data_science_weekly