Last Updated on July 28, 2022
There are many practical reasons why you should choose an online Masters in Business Analytics from the Tepper School of Business at Carnegie Mellon University. We can list facts like: our alumni average $103,000 in starting salary and 84% of our grads secured a promotion or new position within three months of graduation.
However, one of the best parts of this degree is spending two years learning from extraordinarily talented people. Some are students, who make up our close-knit cohorts. Others are faculty, who are leading researchers committed to help students get ahead. For example:
Yan Huang teaches Modern Data Management at Tepper and studies innovative uses for technology in business and entertainment. Her work has examined how an algorithm can increase the time people spend playing video games and why letting employees blog during work can actually be good for a company.
Zachary Lipton directs the Approximately Correct Machine Intelligence Lab while teaching Machine Learning for Business Applications. He’s interested in core machine learning methods and their social impact. He’s also a jazz saxophonist and coauthor of a graphic novel about deep learning.
Param Vir Singh is fascinated by how AI influences businesses and society, especially algorithmic bias, transparency and interpretability. He’s coauthored papers on how Airbnb’s smart-pricing algorithm affects racial economic disparity and the scalability limits of Bitcoin. His research appears regularly in the media, such as an analysis of prerelease piracy’s impact on the box office fortunes of Expendables 3.
Turn Data Obsession Into a Great Career
If working with excellent faculty isn’t enough, then consider your career prospects:
“The demand for data science and machine learning jobs has grown so much that the supply of expertise can’t keep up,” Lipton explained. “In the time that I’ve been in the field, salaries have risen by probably a factor of four or more.”
Those in most demand — and with the most control over their careers — are people who can do the work and translate their ideas into action.
“If you’re really great at mathematics or software development, but you don’t know how to apply those techniques to a business problem, or you can’t communicate to other stakeholders in your organization, you’re not going to be very good at applied machine learning or applied data science,” Lipton said. “The highest demand is for professionals with all three skill sets.”
To learn about the Tepper MSBA, download our program brochure.
Image and article originally from machinelearningmastery.com. Read the original article here.