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IIM Nagpur | Post Graduate Certificate Programme for Advanced HR Analytics (Batch 01)

To transform raw data into actionable insights

Course Snapshot

  • FeeINR 1,30,000/- + GST
  • Work Experience2 - 30 Years
  • Duration6 Months
  • Delivery MethodBlended- Online

Course Detail

Programme Overview:

The Post Graduate Certificate Programme for Advanced HR Analytics is designed to equip you with the skills and knowledge to transform raw data into actionable insights. Through hands-on training, real-world case studies, and expert guidance, you'll become proficient in the latest analytics tools and methodologies. By the end of the programme, you'll be ready to lead your organisation with confidence, making informed decisions that drive excellence and innovation.

With HR Analytics, the future of HR is not just a possibility it's a reality you can create. Welcome to a world where data meets strategy, and insights lead to transformative outcomes.

Programme Highlights

  • Utilising a proven pedagogy developed by the esteemed faculty at IIM Nagpur, refined through industry Programmes.
  • Successful completion of the Programme bestows participants with the prestigious IIM Nagpur Alumni status.
  • Participants will experience 2 days of Intensive Learning at the IIM Nagpur Campus.
  • The Programme incorporates insightful use cases and a discussion-led, hands-on learning approach, culminating in a Capstone Project.
  • The Programme facilitates networking opportunities with industry peers.

Desired Candidate Profile

  • 2 Yrs+ Work Ex. &.
  • 50% marks in UG/PG.

Course Modules

Module 1: Introduction to HR Analytics

  • Understand the domain of HR analytics and its application in modern organizations.
  • Aligning HR Analytics to Organizational Goals, Objectives and HR Strategy
  • Explore the HR analytics continuum and its impact on decision-making.
  • Understand the basics of Analytics and various tools used
  • Learn to design and implement HR analytics projects using evolving HR technologies.
  • Challenges in implementing HR Analytics

Module 2: Descriptive Analytics and Data Cleaning

  • Identify sources of HR Data
  • Capture relevant HR data from various sources and clean the data for analysis.
  • Analyze HR metrics to measure organizational performance and effectiveness.
  • Develop customized HR metrics tailored to organizational needs.
  • Utilize data visualization techniques to communicate HR insights effectively.
  • Implement data governance practices to ensure data quality and integrity.
  • Explore emerging trends in HR analytics and their implications for data management.
  • Case studies and practical exercises on HR data analysis and interpretation

Module 3: Predictive Analytics and Modelling

  • Choose appropriate predictive analytic models for quantitative HR data.
  • Work with qualitative HR data and interpret predictive analytic results.
  • Implement machine learning algorithms and AI for HR prediction tasks, such as employee turnover or performance forecasting.
  • Evaluate the accuracy and performance of predictive models using metrics such as precision, recall, and ROC curves.
  • Incorporate time-series analysis techniques to forecast HR trends and patterns.

Module 4: Prescriptive Analytics and Optimization

  • Apply prescriptive analytics techniques to address HR challenges and optimise processes.
  • Customise solutions based on contextual requirements and stakeholder needs.
  • Implement decision support systems to facilitate data-driven decision-making in HR.
  • Utilize simulation modelling to predict the impact of HR policies and interventions

Module 5 - Workforce planning, Talent Acquisition and Development Analytics

  • Utilise analytics to improve workforce planning, talent acquisition processes and strategies.
  • Analyse employee development data to identify skill gaps and training needs.
  • Predictive Analytics using NLP
  • Develop strategies for talent development and succession planning.

Module 6 - Performance Management and Rewards Analytics

  • Analyse employee performance and potential using predictive analytics models.
  • Employee Engagement Surveys with NLP Sentiment Analysis
  • Understand the relationship between performance, potential, and rewards.
  • Design and implement performance management systems based on analytics insights

Module 7 - Employee Engagement and Retention Analytics

  • Measure and track employee engagement levels using analytics tools.
  • Identify factors influencing employee engagement and satisfaction.
  • Develop strategies to enhance talent engagement and retention.
  • Utilize predictive modelling to forecast employee turnover and attrition rates.
  • Implement employee feedback mechanisms for continuous improvement of engagement initiatives.

Module 8: Culture Fit and Organisational Wellness Analytics

  • Assess value congruence between organisational culture and employee values.
  • Analyse induction processes to ensure cultural alignment and employee engagement.
  • Analyse employee wellness data to identify trends and patterns.
  • Implement strategies for fostering diversity and inclusion within the organizational culture.
  • Utilize sentiment analysis techniques to gauge employee perceptions of organizational culture

Module 9: Introduction to R for HR Analytics

  • Overview of R programming language
  • Data manipulation and analysis with R
  • Statistical analysis and visualization in HR analytics using R
  • Explore machine learning and AI techniques for predictive HR analytics using R.
  • Apply R packages specific to HR analytics

Module 10: Capstone Project

  • Apply learned concepts and techniques to a real-world HR analytics project.
  • Collect, analyse, and interpret HR data using Python, R, and advanced Excel
  • Develop recommendations for improving HR processes and practices.
  • Present findings and insights using Power BI and Tableau.