Engineers Clinic
AdvancedSoftware trackUS-CP-07

Healthcare Claims Fraud Detection

Detect fraudulent claims on imbalanced data with cost-based thresholds, explainability and a fairness audit.

10 Guided Steps480h Internship TierSubmit: GitHub repo or evidence pack + live demo / report + README + milestone logbookVerified CertificateAI Rubric Graded
Program Overview

Detect fraudulent claims on imbalanced data with cost-based thresholds, explainability and a fairness audit.

What you submit

GitHub repo or evidence pack + live demo / report + README + milestone logbook

How it is graded
  • Works as specified30

    Every feature in the brief runs end to end with real data, and the reviewer can follow the README to try it.

  • Code quality & design20

    Clear structure, sensible names, input validation, no secrets in the repo, and a short note on the main design choices.

  • Testing & evidence20

    Automated tests for the core paths, plus a live URL, screenshots or a short demo video.

  • Documentation15

    README covers purpose, setup, how to run tests, and known limits.

  • Reasoning & presentation15

    The write-up explains trade-offs and results in plain language, with numbers where they exist.

Pass 60% · Merit 75% · Distinction 90%

Learning Outcomes
480-hour United States programme. US healthcare claims fraud is a large, well-funded analytics problem.
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.