AI Applications in People Management
Master AI and machine learning applications in HR, from employee engagement to talent management and ethical considerations.
Master AI and machine learning applications in HR, from employee engagement to talent management and ethical considerations.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full AI For Business Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(201 ratings)
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What you'll learn
Master AI applications across the employee lifecycle
Learn to use machine learning for HR decision-making
Understand how to manage algorithmic bias in HR processes
Implement AI solutions for employee engagement and retention
Explore blockchain applications in HR management
Skills you'll gain
This course includes:
4.4 Hours PreRecorded video
4 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course explores the application of AI and machine learning in human resources management. Students learn how to leverage AI for optimizing HR functions, from recruitment to employee engagement and retention. The curriculum covers machine learning fundamentals, rule-based systems, and practical applications in HR decision-making. Special emphasis is placed on addressing challenges like data privacy, algorithmic bias, and ethical considerations. The course also explores emerging technologies like blockchain and their potential impact on HR practices.
The Promise and Potential of AI in HR
Module 1 · 2 Hours to complete
AI Application
Module 2 · 1 Hours to complete
Challenges With Applying AI to HR
Module 3 · 2 Hours to complete
Emerging Solutions
Module 4 · 2 Hours to complete
Fee Structure
Instructors
Professor of Management, Director, Center for Human Resources
Peter Cappelli is the George W. Taylor Professor of Management at The Wharton School and serves as the Director of Wharton's Center for Human Resources. With a focus on human resource practices, public policy related to employment, and talent management, Cappelli has made significant contributions to understanding the dynamics of the workforce in contemporary settings. He holds degrees in industrial relations from Cornell University and in labor economics from Oxford University, where he was a Fulbright Scholar. His extensive experience includes serving as Senior Advisor to the Kingdom of Bahrain for Employment Policy and as a Distinguished Scholar of the Ministry of Manpower for Singapore.Professor Cappelli teaches various courses, including "AI Applications in People Management" and "Managing Social and Human Capital." He has authored several influential books, including The Future of the Office: Work from Home, Remote Work, and the Hard Choices We Face, and has published research in leading journals such as Harvard Business Review and Journal of Business. Recognized as one of the top five most influential thinkers in management by HR Magazine, he is also a regular contributor to The Wall Street Journal and HR Executive magazine. Through his research and teaching, Cappelli continues to shape the discourse on effective management practices in an evolving labor market.
Associate Professor of Operations
Prasanna (Sonny) Tambe is an associate professor of Operations, Information and Decisions at the Wharton School of the University of Pennsylvania. His research focuses on the use of data science and AI for HR applications and on the economics of labor markets for high-tech workers. His research has been published or is forthcoming in a number of academic journals including Management Science, Information Systems Research, MIS Quarterly, The Review of Financial Studies, Industrial and Labor Relations Review, Communications of the ACM,, and Information Economics and Policy. His research has also won a number of awards, including the Best Published Paper in Information Systems Research and the Best Published IS Paper in Management Science. He currently serves on the editorial board of Management Science and was previously on the editorial board of Information Systems Research. Professor Tambe received his SB and MEng in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT) and his PhD in managerial science and applied economics from Wharton.
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4.7 course rating
201 ratings
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