HR Analytics
An advanced, job-oriented course in HR analytics. You learn HR metrics and KPIs, Excel for HR, and how to clean and anonymize HR data. You then analyze headcount, turnover, attrition, recruitment funnels, time-to-hire and cost-per-hire, performance and engagement, compensation, pay equity and absenteeism, and forecast workforce needs. You build Power BI dashboards and HR reports, build a simple explainable predictive model, and use AI tools for interpretation, reports and automation while protecting employee privacy, checking for bias and using AI responsibly. You finish with four portfolio projects, an integrated capstone, interview preparation and practical assignments. All HR data is simulated.
- Duration: 12 weeks
- Fee: Rs 14,999 (about Rs 2,500 a month on EMI)
- Field: Data & Analytics
Roles this track prepares you for
- HR Analyst
- People Analytics Specialist
- HR Executive
- HR Data Analyst
- Talent Acquisition Analyst
- HR Reporting Analyst
- HRIS Analyst
- Workforce Planning Analyst
- Recruitment Analyst
- Compensation Analyst
Curriculum
- HR Analytics Foundations, Metrics, KPIs and Lab Readiness - Learn which decisions HR analytics supports, the correct definitions of core HR metrics and KPIs, where HR data comes from, and the privacy, confidentiality and AI rules that apply from the first day.
- What HR analytics is and the decisions it supports
- HR metrics and KPIs, definitions that matter
- HR data sources, HRIS, ATS, payroll and attendance
- Lab setup and a tour of the sample HR dataset
- Privacy, confidentiality and consent basics
- Rules for using AI assistants with HR data
- Excel for HR Analytics - Use Excel to answer HR questions with conditional counts and sums, dates and tenure, lookups across HR tables, PivotTables and clear charts, and build reusable templates with built-in checks.
- Headcount with COUNTIFS and SUMIFS
- Dates, tenure and age bands
- Lookups across HR tables
- PivotTables for HR questions
- Charts HR leaders can read
- Reusable HR templates with checks
- HR Data Cleaning, Anonymization and Quality - Find and fix dirty HR data, standardize job titles, departments and grades, anonymize and pseudonymize employee data so it can be shared safely, and reconcile the result to payroll headcount.
- Spot dirty HR data and its decision cost
- Clean names, IDs and dates
- Duplicates, blanks and inconsistent job titles
- Standardize departments, grades and locations
- Anonymize and pseudonymize employee data
- Data quality checklist and reconciliation to payroll headcount
- Headcount, Turnover and Retention Metrics - Calculate headcount, FTE, turnover and retention correctly, separate voluntary from involuntary exits, study tenure and first-year attrition and produce a monthly HR metrics report.
- Headcount, FTE and workforce composition
- Turnover rate and how to calculate it correctly
- Voluntary versus involuntary exits
- Retention and tenure analysis
- First year attrition and cohort retention
- Build a monthly HR metrics report
- Attrition Analysis and Retention Drivers - Find attrition patterns by department, role, location, tenure, manager and promotion history, analyze exit feedback, estimate what attrition costs and test whether retention actions work. This module includes portfolio project 1.
- Attrition by department, role and location
- Tenure, manager and promotion effects
- Exit interview and survey text analysis
- The cost of attrition to the business
- Retention actions and testing whether they work
- Present attrition findings to leaders
- Recruitment Funnel, Time-to-Hire and Cost-per-Hire - Measure each stage of the recruitment funnel, time to hire and time to fill, cost per hire and source cost, source effectiveness, quality of hire, offer acceptance and candidate drop-off. This module includes portfolio project 2.
- The recruitment funnel and stage conversion
- Time to hire and time to fill
- Cost per hire and source cost
- Source effectiveness and quality of hire
- Offer acceptance and candidate drop-off
- Write a recruitment effectiveness report
- Employee Performance and Engagement Analytics - Analyze performance ratings and calibration, link performance to tenure and promotion, use goal and productivity metrics carefully, study engagement surveys and training results, and identify high performers and risks fairly.
- Performance rating distributions and calibration
- Performance, tenure and promotion analysis
- Goal and productivity metrics, used with care
- Engagement and survey analytics
- Training effectiveness and learning analytics
- Identify high performers and risks fairly
- Compensation, Pay Equity and Absenteeism Analytics - Analyze pay structures, bands and compa-ratio, compare compensation by role and grade, examine pay equity carefully, study absenteeism, leave, overtime and workload patterns, and write an action memo.
- Pay structure, bands and compa-ratio
- Compensation analysis by role and grade
- Pay equity analysis, done with care
- Absenteeism and leave patterns
- Overtime, shifts and workload signals
- A compensation and absenteeism action memo
- Workforce Planning and Forecasting - Plan workforce demand and supply, forecast headcount, build an attrition-adjusted hiring plan, analyze skills gaps and succession, link plans to the budget and run scenarios.
- Workforce planning basics, demand and supply
- Headcount forecasting methods
- An attrition-adjusted hiring plan
- Skills gap and succession analysis
- Scenarios and the budget link
- Present a workforce plan
- Power BI Dashboards and HR Reporting - Connect HR data to Power BI, model it and write measures, build KPI visuals and filters, design dashboards with privacy and access in mind, produce HR reporting packs and review dashboards for clarity. This module includes portfolio project 3.
- Power BI setup and connecting HR data
- Model HR data and build measures
- KPI visuals and filters
- Dashboard design with privacy and access
- HR reporting packs and automation
- Dashboard review and storytelling
- Predictive People Analytics, AI-Assisted Analytics and Ethical Use - Understand what predictive attrition models can and cannot do, build and evaluate a simple explainable model, check it for bias, use AI to interpret data, write reports and automate workflows, and write a responsible use policy for employee data.
- Predictive attrition, what it can and cannot do
- Build and evaluate a simple explainable model
- Bias detection and fairness checks
- AI for data interpretation and report writing
- AI for workflow automation
- Ethical AI and a responsible use policy
- Capstone, Portfolio, Interview Preparation and Practical Assignments - Combine everything in one end-to-end HR analytics project from anonymized raw data to a validated dashboard and report, then prepare your portfolio, interview answers and practical assignments for HR Analyst, People Analytics Specialist and HR Executive roles. This module includes portfolio project 4.
- Capstone brief, data and plan
- Capstone analysis and validation
- Capstone dashboard and report
- Portfolio case study and resume points
- Interview preparation and practice
- Practical assignments for HR Analyst, People Analytics and HR Executive roles
Frequently asked questions
How long is the HR Analytics course?
It runs for 12 weeks. It is self-paced online learning from EasySkill Career Academy, Surat.
How much does the HR Analytics course cost?
The fee is Rs 14,999, or about Rs 2,500 a month on EMI.
What will I build in HR Analytics?
Every module ends in a graded practical task that AI checks in about 30 seconds, so you finish with a portfolio you can show to employers or clients.
Which roles does HR Analytics prepare me for?
It prepares you to apply for roles such as HR Analyst, People Analytics Specialist, HR Executive, HR Data Analyst, Talent Acquisition Analyst. It does not guarantee a job or income.
Can I learn online, or do I have to visit a centre?
You can learn fully online. EasySkill also has centres in Adajan, Vesu and Bhestan, Surat, if you prefer to visit.
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