AI for Engineering ProductivityCourse

AI Engineering / 5 weeks

AI for Engineering Productivity

Teaches engineering leaders how to use AI to lift developer productivity through copilots, code review, testing, and documentation, with the metrics and controls to keep quality.

Learning path

Six modules with practical application.

  1. Using AI assistants for code, tests, and refactors with the right defaults, controls, and skill development
  2. Using AI to triage diffs, surface risks, suggest improvements, and shorten review time without lowering the bar
  3. Using AI to generate tests, find regressions, and triage flakiness while keeping deterministic confidence in releases
  4. Using AI to draft, update, and search documentation so engineers find answers without breaking flow
  5. Preventing AI from introducing vulnerabilities, leaking proprietary code, or claiming code the team did not write
  6. Measuring the lift honestly: cycle time, throughput, defects, satisfaction, and the impact that survives novelty

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