In the month of September, the class welcomed our analytical tools and techniques term of the program. As the name of the term suggests, each course in this term included more technical knowledge, whether it be statistics, algorithms or coding, to lay the foundation for a data-related position. However, this does not mean we are saying goodbye to the business applications we learned in the intro term, rather we would be learning to apply the more technical skills to better solve the business problem we have seen in the intro term.
The most difficult course of the term, at least to me who was from a not-so-technical background, was taught by Professor Ryan Webb, the course was named Tools for Probabilistic Models and Prescriptive Analytics. In this course, our class learned statistic-based machine learning techniques, dominantly various types of advanced regression-based models. With all assignment written in R, building the model is usually the easiest part, the real challenge comes from the part of tuning and validating the model from reading complicated output tables and graphs, which I would always need to scratch my head hard to get it right. If there is only one thing I learned from this month’s class, then it has to be the famous and important ‘bias-variance trade-off’ which was kind of the theme of the entire month.
I also especially liked Professor Esser’s course, which distinguished itself from any other courses in that it mimicked the situation everyone will likely to face when they get to the workplace. Instead of given a well-specified problem statement as well as materials that are guaranteed to be able to solve the problem, in this course we were given a real-life dataset and were allowed to go whichever direction we like, as long as it delivers value to the organization. The feeling of lost and discouraged in the process of deciding which direction to go surely did not feel good, but it in my opinion is the most important skill that every professional working with data need to know.
Aside from class, our class took good advantage of the abundance of resources provided at Rotman, with one of my favorites being the Self Development Lab. One of our intro term presentations were recorded and sent for analysis by a team of dedicated professional psychologist and presentation coach at the Self Development Lab, after which we would have an appointment with the team and be given really great advice on presentation skills. I was shocked by how accurately they were able to tell I was using a dominant stance during my presentation to hide my actual fear, and I greatly appreciate their advice of engaging the audience to ease the stress which I used every time ever since.
As a vigorous cohort that is always eager to learn, 3 teams of 6 per team from our class including myself participated in one of the largest hackathons during the year, the TD-Elevate tech Jam. We were given a challenge of building something with the use of TD’s Da Vinci API during the hackathon which spans over the weekends. It was definitely an intense weekend with some minimal sleeping time, but in the meanwhile, we had a lot of fun as well as a precious bonding opportunity with classmates which has become one of my most worthwhile memories.
Moving to the end of September, we would soon realize the real hard times of the program both in terms of mental and physical challenges have approached, and I would say it was definitely a good choice to explore as much as possible before that.
The Master of Management Analytics is designed to give students the advanced data management, analytics, and communication skills needed to become an analytics professional.