What you should be able to do
Version data/models
Build CI/CD for ML
Monitor drift
Design rollback paths
Every module is now a full lesson.
Experiment tracking
Make every training run reproducible and comparable.
Model registry
Build a working mental model of Model registry then connect it to implementation evaluation and production trade-offs.
Feature stores
Build a working mental model of Feature stores then connect it to implementation evaluation and production trade-offs.
Serving
Build a working mental model of Serving then connect it to implementation evaluation and production trade-offs.
Monitoring
Observe model and system behavior after deployment.
Drift
Build a working mental model of Drift then connect it to implementation evaluation and production trade-offs.
Governance
Build a working mental model of Governance then connect it to implementation evaluation and production trade-offs.
Projects that prove the skill
Model release pipeline
Use a baseline first then instrument the result and document failure cases.
design with cortex →Drift dashboard
Use a baseline first then instrument the result and document failure cases.
design with cortex →Shadow deployment
Use a baseline first then instrument the result and document failure cases.
design with cortex →How progress is judged
Reliability
Evidence should come from code, results, explanation quality and the ability to identify when an approach should not be used.
Rollback readiness
Evidence should come from code, results, explanation quality and the ability to identify when an approach should not be used.
Operational cost
Evidence should come from code, results, explanation quality and the ability to identify when an approach should not be used.
Turn the track into a personal plan.
Cortex can break this path into daily sessions and adjust based on completed lessons, interview results and your saved learning goals.
Ask Cortex to plan it →