ML Engineering AI Journey
A 12-week learning journey to transform ML engineering workflows using AI tools. Six sprints from context engineering to capstone.
Context Engineering
Write CLAUDE.md for ML projects: model architecture docs, data schemas, experiment conventions, and training configurations.
Weeks 1-2
Workflow Automation
Generate experiment code with AI, automate feature engineering, build test generation for ML pipelines.
Weeks 3-4
Agentic Patterns
Build autonomous experimentation agents, automated model evaluation, and hyperparameter search agents.
Weeks 5-6
Integration & Systems
Connect AI to experiment tracking, model registry, deployment pipeline, and monitoring dashboards.
Weeks 7-8
Advanced Application
Model optimization, production deployment, drift detection, and multi-model system architecture.
Weeks 9-10
Capstone & Transfer
Build a reusable ML tool, experiment template, or team workflow.
Weeks 11-12