AdvancedEngineering trackGB-CP-16
Rail Predictive Maintenance
Detect developing faults in rail assets from sensor data and model the intervention decision against failure cost.
10 Guided Steps240h Internship TierSubmit: GitHub repo or evidence pack + live demo / report + README + milestone logbookVerified CertificateAI Rubric Graded
Program Overview
Detect developing faults in rail assets from sensor data and model the intervention decision against failure cost.
What you submit
GitHub repo or evidence pack + live demo / report + README + milestone logbook
How it is graded
Signals: Milestone gates met; measurable result reported; documentation; deployment or evidence reachable; reflective log
- Functionality & requirements30
- Technical quality & architecture25
- Documentation15
- Deployment & evidence15
- Innovation10
- Presentation5
Pass 60% · Merit 75% · Distinction 90%
Learning Outcomes
240-hour United Kingdom programme. UK rail infrastructure renewal is a major sustained engineering programme.
Target Audience
Engineering Students
Diploma, B.Tech, B.E., BCA, MCA, or M.Tech students seeking practical experience.
Aspiring Developers
Developers who want to build proof-of-work capstone projects for tech resumes.
Job Seekers
Graduates looking for AI-evaluated code review & verified industry credentials.