Unit 1: The 'Why' of DVC: Understanding MLOps Challenges
Unit 2: Getting Started with DVC
Unit 3: Core DVC Operations: Data & Model Tracking
DVC for MLOps: A Beginner's Guide to Data Versioning for ML Engineers
Master DVC to effectively version data and models, build reproducible ML pipelines, and track experiments for robust MLOps workflows.
Unit 1: Building Reproducible ML Pipelines
Unit 2: Seamless Git & DVC Integration
Unit 3: Tracking ML Experiments