Noah

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Noah

Computer Application · KLE Technological University

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Projects

Certified

Self-directed project

Energy and Renewable: Machine Learning for the Power Grid

Junior Machine Learning Engineer · AI / ML · September 2026

92/ 100

A ProoV case study · educational project, not employment

Built a leakage-aware turbine yield predictor end to end: framed TEY as the target, excluded downstream CO/NOX emissions, trained a LinearRegression baseline and a RandomForest model, and validated on a locked-away later-year holdout. The final model achieved about 1.5 MWh MAE and 0.98 R² on unseen data, with a model card that clearly states intended use, limitations, and monitoring guidance.

Graded against

  • Build and validate the model correctly35%
  • Optimize and evaluate honestly25%
  • Write the Model Card (clarity + honesty)25%
  • Explain it to a non-expert15%

Passed · pass mark 60/100

What stood out6
  • Correctly excluded CO and NOX as downstream emissions that would not be available at prediction time
  • Used an earlier-years/later-years split instead of a random shuffle, preserving temporal validity
  • Compared a linear baseline to a tuned RandomForest and judged improvement on held-out MAE
  • Reported held-out MAE, RMSE, and R² and explicitly cautioned against overgeneralizing beyond this plant
  • Leakage-Free Feature Selection
  • Time-Based Holdout Evaluation
The work I submitted19 tasks

11 tasks · 6.9k characters · Python, JavaScript · 8 written answers · 386 words

  • Problem Frame238 characters
  • Leakage Flags113 characters
  • Train Validate BaselinePython · 1.4k characters
  • Train Validate Forest943 characters
  • Train Validate124 characters
  • Tune Evaluate SetupPython · 1.5k characters
  • Tune Evaluate91 characters
  • Residual Read254 characters
  • Drift Monitor94 characters
  • Model Card1.4k characters
  • Teach BackJavaScript · 772 characters
  • Problem Frame23 words
  • Leakage Flags1 word
  • Train Validate Baseline141 words
  • Train Validate Forest76 words
  • Train Validate1 word
  • Tune Evaluate Setup110 words
  • Tune Evaluate1 word
  • Residual Read33 words

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
Certified

Self-directed project

AI-Assisted Code Modernization with IBM

Junior Software Engineer · Software Engineering · August 2026

96/ 100

Based on a public IBM case study · not affiliated with IBM

Built and verified a full legacy-code modernization for KM-Waechter: fixed the wear calculation, handled missing service readings safely, repaired the nightly report, corrected a hidden mileage-conversion bug in the helpers, and added the missing regression test. Also produced a data-driven breakdown-risk analysis that ranked cars using the factors the fleet history actually supported, and documented the AI agent review process in NOTES.md.

Graded against

  • Fix and extend the repo with the agent35%
  • Diagnose the bug20%
  • Direct and audit the AI agent25%
  • Explain it like an engineer20%

Passed · pass mark 60/100

What stood out6
  • Correctly identified the floor-division wear bug and explained why it suppresses a nearly-worn car to 0%
  • Caught the agent changing the 80% rule to 85% and documented the correction in NOTES.md
  • Directed a sweep beyond the obvious tests and fixed the quiet km-to-miles conversion bug
  • Wrote a concrete breakdown-risk analysis that uses km_since_service, avg_daily_km, and load_factor instead of the misleading odometer/age assumption
  • Leakage-Free Bug Diagnosis
  • Directed AI Code Review
The work I submitted20 tasks

12 tasks · 2.2k characters · 8 written answers · 71 words

  • Division Predict73 characters
  • Diagnose Line130 characters
  • Diagnose Why128 characters
  • Scope Prompt66 characters
  • Audit Findings158 characters
  • Audit Why136 characters
  • Acceptance Checklist102 characters
  • Bob Trial Click74 characters
  • Template Repo Click222 characters
  • Verify Report71 characters
  • Exec Pitch452 characters
  • Bob Bonus565 characters
  • Division Predict1 word
  • Diagnose Line10 words
  • Diagnose Why19 words
  • Scope Prompt1 word
  • Audit Findings1 word
  • Audit Why21 words
  • Acceptance Checklist17 words
  • Bob Trial Click1 word

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
2Projects completed
2Verified certificates
94Average score
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