Free Coupon Code Certification in People Analytics and Employee Experience 100% OFF

Udemy Free coupon code for Certification in People Analytics and Employee Experience course taught by Human and Emotion: CHRMI, which has 285 students and is rated 0.0 out of 0 votes. This course is about 10 hour(s) 3 minute(s) in English and was updated on January 19, 2026. You can use this Udemy course with a free certificate and find the coupon at the bottom of this page.

Learn Data Collection and Management for People Analytics, Core People Analytics Metrics and KPIs, Statistical Analysis

Learn Data Collection and Management for People Analytics, Core People Analytics Metrics and KPIs, Statistical Analysis and Tool, Employee Experience Design Framework, Integrating EX with Employee Well-being and DEI

Description

Take the Next Step in Your HR Journey with People Analytics and Employee Experience Design!

Whether you are an aspiring HR professional, a business strategist, an entrepreneur, or a data enthusiast, this course will equip you with the knowledge and practical skills to understand, implement, and apply people analytics and employee experience (EX) design. You will explore how data, analytics, and modern HR tools are transforming organizations — from smarter talent acquisition and predictive workforce planning to improved employee engagement, well-being, and retention.

Guided by real-world examples and hands-on exercises, you will:

• Master the fundamentals of People Analytics and Employee Experience Design, including workforce planning, employee engagement, performance management, and EX frameworks.

• Gain practical experience with HR analytics platforms, AI-powered tools, and case studies to design and evaluate impactful HR and EX strategies.

• Explore real-world applications such as recruitment optimization, attrition prediction, skills gap analysis, well-being initiatives, and leadership development.

• Understand ethical, legal, and governance challenges in people analytics, including privacy, fairness, transparency, and compliance.

• Position yourself for future growth by learning about the latest innovations and emerging trends shaping people analytics, EX design, and HR technology.

The Frameworks of the Course

Engaging video lectures, real-world case studies, projects, downloadable resources, and interactive exercises — designed to help you deeply understand People Analytics concepts, Employee Experience design, and their practical applications.

· The course includes multiple HR case studies and resources such as templates, worksheets, quizzes, reading materials, self-assessments, and hands-on activities to strengthen your ability to apply People Analytics strategies.

· In the first part of the course, you’ll learn the foundations of People Analytics and Employee Experience design, explore the importance of data collection and management, and understand the key metrics and KPIs that shape workforce insights.

· In the middle part of the course, you will develop a strong foundation in statistical analysis, employee experience design frameworks, and advanced People Analytics techniques like predictive analytics, machine learning, NLP, and organizational network analysis.

· In the final part of the course, you will study how to integrate Employee Experience with well-being and DEI, explore technologies and trends shaping the future of People Analytics, and complete a capstone project to apply your learning in a practical, outcome-driven way. Full support will be provided throughout your journey, with queries addressed within 48 hours.

Course Content:

Part 1

Introduction and Study Plan

· Introduction and know your instructor

· Study Plan and Structure of the Course

Module 1: Introduction to People Analytics and Employee Experience Design

1.1. Foundations of People Analytics

1.2. Employee Experience (EX) Design

1.3. Intersection of People Analytics and Employee Experience

1.4. Strategic Implementation

1.5. Future of People Analytics and Employee Experience Design

1.6. Conclusion

Module 2: Foundations of Data Collection and Management for People Analytics

2.1. Understanding Data in People Analysis

2.2. Ethics and Privacy in Data Collection

2.3. Data Management Essentials

2.4. From Data to Insights

2.5. Challenges and Future Outlook

2.6. Conclusion

Module 3: Core People Analytics Metrics and KPIs

3.1. Employee Retention and Hiring Metrics

3.2. Employee Engagement and Experience Metrics

3.3. Diversity, Inclusion, and Mobility Metrics

3.4. Performance and Productivity Metrics

3.5. Implementing Core Metrics and KPIs in People Analytics

3.6. Conclusion

Module 4: Introduction to Statistical Analysis and Tools for People Analytics

4.1. Core Statistical Techniques in People Analytics

4.2. Key Statistical Tools for People Analytics

4.3. Implementing Statistical Analysis in People Analytics

4.4. Conclusion

Module 5: Understanding Employee Experience Design Framework

5.1. Key Components of the Employee Experience Design Framework

5.2. Benefits and Implementation

5.3. Conclusion

Module 6: Advanced People Analytics Techniques

6.1. Predictive Analytics for Workforce Planning

6.2. Machine Learning for Talent Acquisition

6.3. Organizational Network Analysis (ONA)

6.4. Natural Language Processing (NLP) for Sentiment and Engagement Analysis

6.5 Workforce Segmentation for Targeted HR Strategies

6.6. Prescriptive Analytics for Actionable Insights

6.7. Advanced Data Visualization for People Analytics Insights

6.8. Implementing Advanced People Analytics Techniques

6.9. Conclusion

Module 7: Integrating EX with Employee Well-being and DEI (Diversity, Equity, and Inclusion)

7.1. Understanding the Intersections of EX, Well-being, and DEI

7.2. EX, Well-being Key Strategies for Integrating, and DEI

7.3. Challenges and Solutions integration

7.4. Benefits of Integrating EX, Well-being, and DEI

7.5. Conclusion

MODULE 8: Technology and the Future of People Analytics

8.1. Core Technologies Driving People Analytics

8.2. Key Trends Shaping the Future of People Analytics

8.3. Tools and Platforms for People Analytics

8.4. Challenges and Considerations

8.5. Conclusion

Part 2

MODULE 9. Capstone Project