Model Development — Databricks Certified Machine Learning Associate

Official references for this objective

• Databricks — Building a Foundation Model for Energy on Databricks with Applied Computing | Databricks

  an AI model that is both physics-informed and domain specific

• Databricks — Accelerating AI From Model to Impact at Workday With Databricks Apps | Databricks

  Workday compressed delivery to weeks, launched three production AI applications in a single year, and scaled its flagship Sales Companion to 4,500+ active users

• Databricks — Dr. Jekyll and Mr. H-AI-de: Using MLflow and AI Judges to measure model alignment and safety | Databricks

  Emergent misalignment sent shockwaves through the AI community in 2025. We discovered that a model fine-tuned on narrow tasks could suddenly pivot from a "helpful

• Databricks — A Simple, Managed Platform - Modern Feature Engineering on Databricks | Databricks

  Define what a feature is (source, entity, aggregation, time window) and let the platform compute it correctly in every context.

• Databricks — From Training to Production: MLOps for Deep Learning on Databricks | Databricks

  distributed training with MLflow tracking, model registry workflows for large models, GPU-aware serving with traffic splitting and autoscaling

• Databricks — High-Throughput, Low-Latency: The Databricks Playbook for Production Model Serving | Databricks

  autoscaling strategies, and optimizations across GPU/CPU utilization, request routing, and caching that enable sustained high throughput without sacrificing latency or cost

• Databricks — How Databricks Apps Facilitated Model Retraining | Databricks

  in 3 weeks, a fully-fledged computer vision labeling application could be built using apps, saving our retread SMEs months of manual effort