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HR Analytics Dashboard for Predictive Attrition (Tata-Style)

Target year: MMS Sem 4 (Capstone / Dissertation) AICTE: 6 credits · ~150 hrs Bloom: Create / Evaluate MU CBCS: HR402 Capstone / Dissertation

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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Core skills

About this project

Build an HR-analytics dashboard predicting employee attrition risk for a 2000+ employee company. Use historic exit data + engagement scores + performance + tenure. Train ML model (logistic regression + random forest). Wrap in Tableau/Power BI dashboard for HRBPs. Address bias + ethics.

Course Learning Outcomes (CLOs):
CLO1: Apply ML to a real HR business problem.
CLO2: Engineer features from messy HR data.
CLO3: Build dashboards that translate ML outputs for non-technical HR.
CLO4: Audit model fairness across gender/department/tenure.
CLO5: Communicate predictive insights + ethical caveats.

Industry/societal relevance: People-Analytics teams at Tata (Tata Steel, TCS), Reliance, Infosys, ICICI are hiring 100+ HR analysts. Strong placement-link.

Milestones

1. Data Acquisition + Cleaning

15 marks 21d

Pull 3 yrs HR + exit data from partner (anonymized). Clean + feature-engineer. Submit data dictionary.

2. Baseline Logistic Regression

20 marks 18d

Train logistic regression to predict 12-month attrition. Report AUC + interpret coefficients.

3. Advanced Models

25 marks 21d

Random Forest + XGBoost. Report on test set. SHAP for explainability.

4. Tableau / Power BI Dashboard

20 marks 21d

HRBP-friendly dashboard: cohort attrition risk, drill-down by department, top-3 reasons. UX-tested with 3 HRBPs.

5. Bias Audit + Final Defense

20 marks 19d

Fairness across gender + dept. 14-page report + ethics section. Oral defense.

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Skills you'll learn

HR AnalyticsPredictive Modeling (logistic regressionRFXGBoost)Feature engineeringTableau / Power BIML ethics + bias auditingStakeholder dashboard design

Tools used

Python (Pandas + scikit-learn)Tableau Desktop (student) or Power BI DesktopSQLExcelGitHub

Prerequisites

HR Management; basic ML / statistics; SQL; partner company data access

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HR Analytics Dashboard for Predictive Attrition (Tata-Style)

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