Professional Courses

This module provides a comprehensive foundation in Human Resource Management and introduces the role of analytics in modern HR practices. Participants will gain an understanding of how data-driven approaches support effective decision-making across the employee lifecycle.

Topics:

• Fundamentals of Human Resource Management
• Strategic Role of HR in Organizations
• Introduction to People Analytics
• Basics of Statistics for HR Analytics
• Framework for Problem Solving:
  • Define the Problem
  • Collect Data
  • Build the Model
  • Evaluate and Critique the Model
  • Present Results and Benefits
  • Deploy the Model
• Critical Stages of the Talent Life Cycle

Case Study:

• HR Decision Making: Issue Identification and Problem Solving

This module focuses on key HR practices and the application of analytics and AI to evaluate and enhance organizational performance. Participants will explore how benchmarking, data visualization, and AI-driven insights support effective HR decision-making across the employee lifecycle.

Topics:

• Understanding Important HR Metrics Across the Employee Journey
• HR Valuation Techniques and Workforce Analytics
• Benchmarking: Concepts, Methods, and Best Practices
• Dashboarding of KPIs using tools such as Tableau and Excel
• AI-Enabled Insights for Performance Management
• Performance Management and Goal Setting
• Providing Effective and Data-Driven Performance Feedback

Case Study:

• Performance Management and Feedback: Practical Application and Analytical Insights

This module explores how Artificial Intelligence and analytics are transforming talent acquisition and employee development. Participants will learn how AI-driven insights enable smarter hiring decisions, improve prediction of employee performance, and enhance the effectiveness of training and development initiatives.

Topics:

• Key Factors in Selection that Determine Quality of Hire
• AI-Driven Screening and Candidate Shortlisting
• Predicting Employee Performance using AI and Data Analytics
• Measures to Track: Introduction to Predictive Analytics
• Evaluating Talent Acquisition Effectiveness
• Employee Training and Development Analytics using AI

Case Study:

• AI-Enabled Hiring and Learning Systems: Improving Quality of Hire and Employee Development Outcomes

This module explores organizational culture, employee onboarding, and the role of AI in ensuring alignment between individual and organizational values. Participants will learn how data-driven approaches can enhance the onboarding experience and improve culture fit.

Topics:

• Understanding Organizational Culture and Types of Cultures
• Employee Socialization Process and Stages of Onboarding
• Designing AI-Driven Onboarding Models
• Creating an Onboarding Predictive Model
• Concept of Value Congruence and Its Impact on Performance and Retention
• Using AI to Assess Culture Fit and Employee Alignment

Case Study:

• Enhancing Onboarding Effectiveness and Culture Fit using Predictive Analytics

This module focuses on understanding employee engagement and how AI-driven analytics can be used to measure, monitor, and improve engagement levels across the organization. Participants will explore key drivers of engagement and learn how data can support proactive HR interventions.

Topics:

• Importance of Employee Engagement in Organizational Success
• Major Drivers of Employee Engagement
• Designing and Analyzing Employee Engagement Surveys
• AI-Based Sentiment Analysis for Employee Feedback
• Variations in Employee Engagement Across Days and Work Patterns
• Measuring Employee Engagement at Team and Organizational Levels

Case Study:

• Using AI to Monitor and Improve Employee Engagement and Team Productivity

This module explores how collaboration drives team effectiveness and how AI-powered analytics can be used to understand and improve team dynamics. Participants will learn to analyze collaboration patterns and leverage organizational network insights to build high-performing teams.

Topics:

• Understanding Collaboration and Its Importance in Organizations
• Analyzing Collaboration using Data and Analytics
• Introduction to Organizational Network Analysis (ONA)
• AI-Driven Insights into Team Communication and Interaction Patterns
• Identifying Collaboration Gaps and Bottlenecks
• Intervening in Organizational Networks to Improve Team Effectiveness

Case Study:

• Using Organizational Network Analysis to Build High-Performing Teams

This module examines how organizations can leverage analytics and AI to evaluate employee performance, identify high-potential talent, and design effective reward systems. It focuses on enabling fair, data-driven decisions that align individual contributions with organizational goals.

Topics:

• Understanding Jobs, Roles, and Competency Frameworks
• Performance vs. Potential: Key Decision-Making Dilemmas
• AI-Driven Performance Evaluation and Talent Segmentation
• Identifying High-Potential Employees using Predictive Analytics
• Rewards and Recognition: Key Considerations
• Data-Driven Approaches to Compensation and Benefits

Case Study:

• Balancing Performance, Potential, and Rewards using AI-Enabled Analytics

This module provides a deep dive into the factors influencing employee attrition and explores how AI and analytics can be used to predict, prevent, and manage talent turnover. Participants will learn to design effective retention strategies based on data-driven insights.

Topics:

• Understanding Why Employees Leave Organizations (Attrition Analysis)
• Key Drivers of Employee Turnover
• AI-Based Attrition Prediction Models
• Talent Retention Strategies and Best Practices
• Personalized Retention Interventions using Analytics
• Measures to Track: Retention Metrics and KPIs

Case Study:

• Using AI to Predict Attrition and Improve Employee Retention Strategies

This module focuses on the importance of employee wellness and workplace safety, and how analytics and AI can be leveraged to design effective wellness programs. Participants will explore best practices and learn how data-driven insights can improve employee well-being and organizational productivity.

Topics:

• Understanding Employee Wellness and Its Importance
• Health and Safety in the Workplace
• Employee Wellness Program Best Practices
• Key Metrics for Measuring Employee Wellness
• Using Predictive Analytics to Optimize Employee Wellness Programs
• AI-Driven Insights for Proactive Health and Safety Management

Case Study:

• Enhancing Employee Wellness and Workplace Safety using Analytics and AI

This module equips participants with practical skills in data analysis and business intelligence using Power BI, integrated with AI capabilities. It focuses on transforming raw data into meaningful insights to support strategic business and HR decision-making.

Topics:

• Introduction to Business Intelligence and Power BI
• Enhancing Analytical Skills using Power BI for Business and IT Applications
• Data Modeling and Data Visualization Techniques
• Integration of Data from Multiple Sources (Relational and Non-Relational)
• Creating Interactive Dashboards and Reports
• AI Features in Power BI for Advanced Analytics
• Report Management and Deployment Strategies

Case Study:

• Building Interactive HR Dashboards for Data-Driven Decision Making