[UMN MSBA] Some Reflection on Courses in Summer Semester
On the final day of the summer semester, after having some decent dinner with friends, I finally came home and started writing some notes and reflections about the summer semester. It is a hard time to conclude everything in a few paragraphs, but I really want to spend some time putting down some of my feelings on courses, on my growth and on what I still lack.
I tried to answer the question first: Who is suitable for UMN MSBA? Not so sure about the answer, but I tried to conclude in few points:
1. The one who has working experience for several years. I think with some business sense and trained by the real business world, the person can start learning how to survive in UMN MSBA.
2. The one who is not afraid of analysis and even enjoy the process of finding insight from data. I think you don’t have to be experienced in coding or other analytical tools, but a least in your life before coming to UMN, you have to get some contact with analysis in certain extent.
3. The one who wants to find a job in U.S. I can say training in UMN MSBA is good enough to let you pivot to your career. Even though it is still summer, we didn’t learn much. The courses here are really well designed and kind of like a professional cram school.
Who is not suitable for UMN MSBA?
1. I think some professional or senior software engineers are not that suitable for MSBA. The training here is technical, but not that technical to make a software engineer more professional to compete with another graduate from other CS background. And since you already know how to code well and perfectly, why you have to spend another year reviewing the things you already know?
2. The person who is unwilling to share and participate in group discussion is not suitable for MSBA. In summer we experience tons of discussions. How to manage the group dynamic is really a big deal. We can learn so much from our teammates, but if you are afraid of sharing and engaging in groups, you can barely learn anything.
After the sharing, let’s dig right into the courses. I’d like to give each course some scoring and to share how I feel about the course, hoping to presenting some interesting and valuable information to those who are interested in UMN MSBA.
a. Programming and Application Development
General Level: 7/10
Growth Level: 9/10
Breakdown Level: 10/10
This course is very technical. We learnt python from 0 to 0.5 in 10 weeks. Instructor admires the methodology of flipped classroom, which means we need to read through all the material provided by the course. For me, it is not a good way to learn and grow, but after the summer, I start to know it is a must for so many chapters need to be covered. Forcing student to self-learning is an evil must.
The homework loading for the course is gigantic, which leads to tremendous growth but also tremendous breakdown. We have seven assessment prior class, nine lab homework after class, 3 programming challenges, two quizzes, one midterm, one final and one trend marketing presentation.
Being exposed to such great amount of homework sometimes carries me away. I faced my first breakdown when I dealt with the lab with the topic ‘Class’, and the second was followed by the week when the challenge and midterm were colliding with each other. However, they train me to open Anaconda as an instinct instead of as a painful to-do-list.
In the 2nd half of the course, we dove in the world of NumPy and pandas, which lead us to data science. We were able to load in data and clean the data. That is a really intriguing world for me. I just felt like that I was wondering out of the gate of data science for so long before I get here, but it the last month of summer term, I finally went through the gate and see the whole new world.
General speaking, I didn’t appreciate the flipped classroom structure of the course and the fact too many tasks were flocked together; but I enjoyed the growth after 10 weeks with the aid of these loads which enabled me learn coding so fast.
b. Financial Accounting
General Level: 9/10
Growth Level: 9/10
Breakdown Level: 8.5/10
Financial Accounting is my favorite course in the semester, and probably in my top 5 list among all the course I took since college. The instructor is so knowledgeable and really make the most of the course time, unlike other instructor with relatively loose structure of the course.
We didn’t learn the traditional guideline of accounting. Instead we learn how to collect data, make reasonable judgement based on the data, and always be skeptical of the data at hand. We talked through how accounting regulations and the operation of the companies influenced the business world, which is so fascinating. The instructor granted us the viewpoints and a kaleidoscope of how we can use data.
The loading of the course was moderate in the first half of the term: one case a week. With capable team members, they were not a big deal. However, thing went to the fringe of breakdown after the take home midterm. (That’s the reason I scored it 8.5 out of 10 for the breakdown level) It took us about 10 hours to finish the midterm. And the assignment after midterm was a real torture. Two data assignment in a row really pushed me to limit. I spent nearly 15 hours on each. The datasets were big. And it was the very first time, I tired to use python and R as tools to conduct modeling and analyses. Though it was horrible, it turned out to be the most interesting and most growth boosting project I had ever done. I learned so much from these two assignments and the project followed by, which we use the same kinds of model to tackle with. It was presentable, it was full of depth and many inspiring elements, and it was useful for my portfolio.
General speaking, the course is solid-constructed. The instructors are serious about the course planning and really want us to learn a decent amount of skills and knowledge from him. And he executed this really well.
c. Marketing Management
General Level: 5/10
Growth Level: 4/10
Breakdown Level: 3/10
The course is designed in such a loose manner. Instructor is very experienced in the related field, but he somehow was not able to transfer his experience into teaching.
The most annoying part of the course was the overloaded assignments which couldn’t initiate any extent of growth. We had 3 discussion forums, 3 journal entries, 5 team discussion reports, 1 market simulation projects, numerous quizzes, 1 final project and 1 final exam. They were so trivial and all I decided to tackle these assignments was trying to finish them as soon as possible. In the very beginning, I managed to maintain my quality of writing the assignments, but I just gave up when the semester proceeded. It was really a striking contrast to financial accounting class, which was with moderate loading of assignments and lots of chances to grow.
General speaking, I didn’t learn much from the course. It was just like the early version of the marketing course I once took in Taiwan, with entry level but not inspiring enough.
d. Analytics for Competitive Advantage
General Level: 6.5/10
Growth Level: 7/10
Breakdown Level: 6/10
The course is kind of like analytics 101 for the MSBA student. As an introductory course, the professor quickly brought us through different kinds of analytics pillar, such as descriptive, causal, predictive and unsupervised learning. Most of the teaching was focus on the introduction of these techniques, preparing us for the more professional course in the following fall and spring semester.
The major components of the course were 3 business case from Harvard and 3 analytical cases from Carlson School, plus the live case collaborated with Mall of America. The cases were fair enough. Thanks to the great help from team members, we were able to go through cases smoothly. The only frustrating part of the case discussion is that the instructor was not willing to share codes with us. I think it was strange because with the limited time, we’d like to learn as much as we can by mimicking and copying pasting. So far, I can’t still get to know the logic behind the unwillingness of code sharing.
For the live case, it was frustrated but not overloading. I seemed to be too focused on analytics rather than giving insightful recommendation. We dwelled too much on a perfect model. This was a big lesson to me. Treating the client as Mall of America, we should get actionable items with moderate analyses, making them interpretable and easy-to-understood. Making an ultimate model granted little influence. Business Analytics, where business is put before analytics, we should always purse the value we can generate for business instead of pure analytics.
General speaking, the instructor is such a free-style person, which led to a free-style course pattern. We usually had 2.5-hour course rather than the 3.5-hour full length. He emphasized business value over analytical model, story over techniques. You can score high if you follow his logic and belief, but I bet there is probably some collision for the following semesters. He laid a fair fundamental for the professional courses afterward, but I just don’t learn much from the course.
e. Introduction to Statistics for Data Science
General Level: 5.5/10
Growth Level: 5/10
Breakdown Level: 5/10
The course is an introductory course for statistics, starting from mean/standard deviation to multiple regression model. Instructor admires the flip classroom as well. We needed to finish his recording on the material posted on the system every week before course. During the course, we finished about two exercises, and the course ended.
The instructor emphasized the interpretation for some of the statistics. It was very ambiguous for me at the very beginning, but it turned out to make some sense with the semester proceeded. The work load was fair with simple quizzes after course, midterm, final and an easy project on regression. However, I think the instructor should teach us more and give some more challenging tasks for us. Prior to the beginning of the term, I think this course will be intense and we could learn how to use R and better our understanding of the tool through the course. However, my expectation fell in the end.
General speaking, I didn’t achieve the growth I expected. The course was like a dish without spices. We absorbed it, but it tasted so plain.
Last, I’d like to end the article with a two-dimension graph to conclude my reflection on the semester. Overall, with some up-and-downs in courses, I feel so blessed I came to UMN to pursue my MSBA degree. It is a good program overall, based on the first semester. I grow, I learn a lot, I push my limit, and I am looking forward to the coming term to see a bigger world of analytics.
