Chris Anderson is a professor at the Cornell Nolan School of Hotel Administration. Prior to his appointment in 2006, he was on the faculty at the Ivey School of Business in London, Ontario, Canada. Professor Anderson’s main research focus is on revenue management and service pricing. He actively works in the application and development of revenue management across numerous industry types, including hotels, airlines, and rental car and tour companies, as well as numerous consumer packaged goods and financial services firms. Professor Anderson’s research has been funded by numerous governmental agencies and industrial partners. He serves on the editorial board of the Journal of Revenue and Pricing Management and is the regional editor for the International Journal of Revenue Management. At the Nolan School of Hotel Administration, Professor Anderson teaches courses in revenue management and service operations management.
Leveraging Predictive AI in HospitalityCornell Course
Course Overview
As a hospitality professional, it's essential to quickly understand how AI can enhance your daily operations as well as improve both customer and employee experiences. This process begins with establishing a foundation in predictive analytics and machine learning, which utilizes historical data to forecast, make recommendations, and support decision making. Understanding these practices is crucial for staying competitive and responsive in a rapidly evolving industry landscape.
Throughout this course, you will delve into how AI is transforming the hospitality sector, exploring both the opportunities and challenges it presents. A focus will be placed on how machine learning can be leveraged to optimize customer experiences and enhance employee performance and operational efficiency. You will apply predictive analytic models to evaluate and optimize analytical processes, analyze qualitative and quantitative data to make informed predictions, and evaluate correlations among variables. You'll also select suitable predictive models, assess their performance, and refine these models to more accurately forecast market demands and business outcomes while identifying data biases and their potential impact on model limitations.
By the end of this course, you'll have explored, practiced, and evaluated various methods of integrating machine learning and predictive analytics into your organization. These skills will assist in streamlining business activities, supporting organizational goals, and allowing employees to focus more on enriching the customer experience. Although the course includes numerous AI use cases, they are intended as foundational learning; you are encouraged to build upon these models and apply your skills to effectively address data-driven challenges as they arise in your professional environment.
Note: Coursework will require access to Microsoft Excel, a free trial version of BigML, and free versions of ChatGPT, Zapier, and Botster.
Key Course Takeaways
- Analyze potential bias in employee data based on education, gender, experience, and salary
- Predict the probability of customer cancellation
- Create marketing and communication opportunities by grouping customer, financial, employee, and resource data into clusters
How It Works
Course Author
Who Should Enroll
- Mid- and senior-level hospitality professionals
- Marketing and sales directors in hospitality
- HR directors for hospitality organizations
- Business analysts
- Hotel general managers
- Housekeeping directors
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