1. DS/ML Projects – Initial Setup
  2. ML Projects Lifecycle
  3. ML Architecture – Framework and Components
  4. Data Exploration and Quantifying Business Problem
  5. Training & Testing ML model
  6. ML model performance measurement
  7. CRUD operations with different JavaScript frameworks
  8. Feature Store
  9. Building ML Pipeline