This Data Competition was hosted by UT's Business Analytics Association (BAXA), and it involved a compilation of SQL, Python, Meta Data, Machine Learning, Probability, and Optimization/Logic problems. The goal was to complete all of the problems as fast as possible.
This competition was essentially a virtual escape room that was set up as a series of technical problems, and the teams that finished first would win. We didn't know this at first, but there were actually many technical issues with the competition. The entire competition was coded by a member of BAXA which is incredibly impressive, but of course, there were countless technical issues as this was something he was new to and it's incredibly difficult for one person to code all of that. The competition could not be done on a Macbook (the only device I had with me, so I was bouncing between different devices trying to complete the competition however I could) and it would crash at different times for some people and not for others. So overall, we definitely had to make do with the technical complications, but the unique style of the contest made it incredibly interesting and enjoyable.Â
Everyone immediately started coding as fast as they could, and the competition started out with some basic Python data science problems to uncover a specific key within a string, and this key could then be used to move on to the next problem. The next problem involved Meta Data and uncovering patterns that we wouldn't normally notice, then there were SQL Questions involving intermediate to advanced operations. Wait come after was uniquely interesting, it was a bonus question about optimization and decision-making. We had to look at a series of options and determine a combination that would satisfy the requirements listed. After this was another unique type of problem, it involved a logical combination of various patterns that were given to us on paper, and we had to essentially beat an "AI" at Rock-Paper-Scissors by figuring out its play style. The last two questions were the most advanced. There was some machine learning in Python as well as using a Ceaser Cipher to encode and decode certain values to get the final code phrase to officially "Escape McCombs."