7:20 AM – Wake Up
7:20 – 8:00 AM I aim to exercise at least twice weekly to relieve the tension from sitting for long periods.
8:00 – 8:45 AM After a quick shower, I enjoy the breakfast I prepped the night before to save time. I pack my essentials: laptop, lunch, extra clothes, and head out for the walk from Wolf Ridge to the Institute of Advanced Analytics (IAA). MSA students are expected to wear business casual most weekdays, so I make sure to pick out my outfits the night before to save time in the morning. The fresh morning breeze on my face feels rejuvenating, a perfect start to the day.
During the walk, I often rehearse conversations with teammates in my head, anticipating different outcomes. This helps me prepare for real interactions later on.
8:45 – 9:00 AM Once I arrive at the institute, I quickly store my lunch in the fridge. Before class begins, I use this time to catch up with classmates, have small talks, or drop by a quick office hour with questions.
9:00 – 10:15 AM The first class of the day is the Analytics Foundations lecture with Dr. LaBarr. I take notes on the slides, marking areas that need further clarification or practice. The lecture covers various statistical methods directly applicable to our ongoing summer practicum project on airline data.
10:15 AM – 12:00 PM After the lecture, we dive into a breakout session and lab to reinforce the concepts we’ve just learned. I ask as many questions as possible.
12:00 – 12:30 PM Lunch time! After heating my lunch, I head outside to The Corner, a grassy area next to the Institute with several colorful shipping containers used for socializing. One of the spaces even has a piano, which I sometimes play.
12:30 – 1:00 PM After relaxing, it’s time for a quick summer practicum meeting. Our team of five discusses our progress and any challenges we’re facing. Everyone is supportive, offering plenty of help and encouragement as we work through problems.
1:00 – 2:15 PM The next class is a programming lecture with Dr. Healey. His lectures on syntax and logic are beneficial, especially for the programming aspect of our summer practicum, where we handle data manipulation and structure.
2:15 – 4:00 PM After Dr. Healey’s lecture, we move into self-paced programming assignments. The lab consists of conceptual programming questions to assess our understanding. Once I finish the assignment, I will use any extra time to revisit our summer practicum discussion, focusing on areas that need debugging or planning new tasks for the evening. This meeting typically lasts about an hour.
4:00 – 4:30 PM I walk back to Wolf Ridge and take a short break to relax.
4:30 – 5:30 PM Study time. I first tackle any unfinished work from Analytics Foundations or programming assignments since they’re due by 11:59 PM. This is also an excellent opportunity to digest the concepts I’ve learned today.
5:30 – 6:30 PM Nothing beats a homemade bowl of noodles with meat and vegetables. I often chat with my roommate over dinner and wash the dishes right after.
6:30 – 10:30 PM I like to set 40-minute study sessions with 5-minute breaks during this time. I wrap up anything that still needs to be done. For concepts that didn’t quite click during the lecture, I rewatch Panopto recordings and take detailed notes. I also update my calendar and check Slack for any important messages.
During one of these study blocks, I made progress on the Python certification courses, which complemented the material covered in Dr. Healey’s Python class.
10:30 – 11:00 PM After a productive day, I unwind with some stretching exercises before heading to bed. Sleeping at least 7 hours is crucial for staying sharp and ready for the next day.
Columnist: Lucy Liu