Name: Data Analytics in Hospitality: Applied Data Science Using No-Code Analytics
Start: 2024-05-31T17:30:00-07:00
End: 2024-06-02T17:00:00-07:00
Location: UNLV Hospitality Hall, Room 234

Join us for an exciting 3-session, in-person course in which we will dive into the world of Data Analytics and the wonders of Applied Data.
About this Event

Data Analytics in Hospitality: Applied Data Science Using No-Code Analytics

During this 3-session bootcamp-style course, we will explore the power of data analytics in the hospitality industry and learn how to apply data science without any coding. This event is perfect for anyone interested in leveraging data to drive business decisions and gain a competitive edge in the hospitality sector.

Data Analytics (DA) is an intimidating subject for many of us. One of the goals of this course is to demystify DA and make it accessible for everyone to understand and use regardless of their career path. This comprehensive introductory course will cover:

Database Querying
Predictive Analytics
Data Mining
Dashboard Creation
Data Visualization
…and more!

You will learn various data science methods such as classification, regression, clustering, dimensionality reduction, interpretable AI, text analytics, time series, and image analytics. These techniques can enable you to conduct analytical tasks such as predicting booking cancellations, classifying hotel reviews, and customer segmentation. What differentiates this course from others is that we will be using completely free business intelligence software which requires little to no coding.

This course is heavily applied, which means that instead of focusing on deeply understanding why the algorithms work, we focus on how to use the algorithms and interpret the results. This is a field with a lot of career opportunities with a projected growth rate of around 35% annually and a median salary of ~$100K (https://www.bls.gov/ooh/math/data-scientists.htm).

Analytics is used in essentially all functional areas in the Hospitality industry such as human resources, information technology, finance, revenue management, supply chain management, and marketing. A career in analytics is also a popular entry point for leadership positions since executives as far up as the CEO use data to make better decisions. By the end of the course, you will have an analytics portfolio that you can submit along with your resume and cover letter to potential employers.

This course is hands-on in the computer lab on campus. You will learn data science methods including: