Table of Contents

  1. Introduction to Data Engineering for AI/ML 
  2. Lifecycle of AI/ML Data Engineering 
  3. Architecting Data Solutions for AI/ML 
  4. Technology Selection in AI/ML Data Engineering 
  5. Data Generation and Collection for AI/ML 
  6. Data Storage and Management in AI/ML 
  7. Data Ingestion and Preparation for ML 
  8. Transforming and Processing Data for AI/ML 
  9. Model Deployment and Data Serving
  10. Security and Privacy in AI/ML Data Engineering 
  11. Emerging Trends and Future Direction