Thursday, September 29, 2022
7:45 A.M. – 8:45 A.M. Wake up
I start my mornings usually around 7:45. After eating breakfast and doing my usual routine, I pack my bags and get ready to leave for the Institute for Advanced Analytics (IAA).
8:45 A.M. Leave for the Institute
I’m fortunate to have a car, and I live not too far from the Institute, so I leave about 15 minutes before the start of my first class at 9. There are several classmates who commute much further distances than me by car or bus.
9:00 A.M. – 10:15 A.M. Data Mining Class
My first class of the day is Data Mining. For most of the classes, I am with members of the Orange Cohort. The IAA splits all the members of the program into two roughly equal cohorts, Blue and Orange. This ensures that most classes are not too large, which better increases students’ learning and understanding of the material.
This is our first Data Mining class, where we learn a broad array of statistical techniques that we will use, including Bootstrapping, which I first learned about in my undergraduate classes. Coming from a strong mathematics and statistics background, I am often at least somewhat familiar with most of the material, but just not to the depth at which some of the materials are taught at the Institute.
10:20 A.M. – 10:40 A.M. Ethical Considerations for Data Professionals
After class, our Practicum Team has a meeting to go over our Ethical Considerations One Page Document regarding our Practicum project. At the IAA, the Practicum is a large part of the curriculum. It is an eight-month long team project with a real company working on a real-world data problem. Companies can span many different industries, from sports teams to government agencies to everything in between.
During this specific meeting, we go over my team’s one-page document that outlines potential ethical considerations with our practicum project. It is important to note that the IAA doesn’t just educate students on technical data science skills, but really emphasizes soft skills such as communication and being an ethical data storyteller. These skills are just as, if not more, important than the technical skills we are developing. The best conclusions from a data project mean nothing if the process wasn’t ethical and if the audience doesn’t comprehend the results.
10:40 A.M. – 10:45 A.M. Kitchen Duty
Every week at the IAA, two Practicum teams are assigned kitchen duty to keep the communal kitchens clean. While cleaning, our team works out when and where we’re meeting next. It can sometimes be difficult to find a meeting time that everyone agrees on with no scheduling conflicts.
10:45 A.M. – 11:30 A.M. Studying
I have a gap in my schedule until 11:30, so I find a quiet place and do some light studying of some of the material from my classes. It’s important to fill gaps in the schedule at the IAA, because the class material can move fairly quickly and time at the Institute is valuable.
11:30 A.M. –1:00 P.M. Homework Team Meeting
This is my first meeting with my new homework team. While the Practicum team remains constant throughout the year, homework teams change every module, which is five weeks. After short introductions, we plan out how we will complete some of the assignments that will be due this module. We then work on our Text Analytics Project Proposal, applying information about Python and Natural Language Processing we just learned in our Text Analytics Class the previous day.
1:00 P.M. – 2:30 P.M. Lunch
After the meeting, I eat lunch. Lunchtime is an excellent time to socialize at the Institute. I usually eat a packed lunch, but a lot of the students get food from a food truck outside the building. Every day, there’s a different food truck, which can have very different kinds of food than the day before. Most students eat lunch downstairs, where there’s a number of board games to play as well as a ping pong table. My fellow classmates have really gotten into playing ping pong — there was a ping pong tournament over the summer among students.
Furthermore, sometimes during lunch, there are MSA Share20s. These are presentations in which students can voluntarily present on a wide range of topics, some related to data science and some not. These are excellent opportunities for a student to share something they’re passionate about, other students to learn something new, and for students to improve their presentation skills.
2:45 P.M. – 4:00 P.M. Introduction to Colour Class
The Colour Class is the first class to occur outside of the Alliance Building. It’s at the Visualization Lab at Hunt Library, which is a short walk from the Institute. During this lecture, we learn about the history and use of color, as well as how to effectively use color in data visualizations.
4:00 P.M. – 6:30 P.M. Home and Mental Break
After a long day at the Institute, I drive home and relax for a little while. It’s important to rest and take mental breaks because the class material and work from the Institute can be daunting at times.
6:30 P.M. – 9:00 P.M. Workout and Rest
After taking an extended mental break, I go to the gym to workout. In a stressful program like the MSA, it’s important to keep your body active in whatever way you see fit. This helps physical as well as mental health. For me, going to the gym is an excellent stress reliever that I enjoy doing.
After my workout, I rest for a little bit before eating dinner.
9:00 P.M. – 10:00 P.M. Dinner and LinkedIn Update
While I eat my last meal of the day, I do some light scrolling on LinkedIn. I see a couple of posts from my classmates as well as alumni I’ve connected with. The IAA has a large number of alumni, and I’ve connected with some of them on LinkedIn, expanding my professional network.
I then update my LinkedIn to include a project I did. The IAA places an emphasis on using LinkedIn as a way to not only connect with classmates and alumni, but also potential job recruiters.
10:00 P.M. Nighttime Routine and Sleep
Finally, I wind down for the night and start my nighttime routine. Eventually, I fall asleep, ready to begin another day at the Institute for Advanced Analytics.
Columnist: Grant McMasters