Discover how to manage the complete machine learning lifecycle using MLflow in this beginner to intermediate-level workshop. Learn about MLflow Tracking to record and query experiments, MLflow Projects for reproducible runs, MLflow Models for diverse deployment, and Model Registry for collaborative lifecycle management. Explore the MLflow UI to visually compare experimental runs and evaluate metrics. Gain hands-on experience with practical examples and prepare to enhance your machine learning development process. This 58-minute session is the first in a three-part series, focusing on an introduction to MLflow and its key components.