GRADUATE SCHOOL
[CMU MISM-BIDA] Attending Graduate School at CMU in Spring 2022
Concluding CMU, leaving Pittsburgh!
A-Ha-Hahaha — Kawhi Leonard
Preface
I’ve always hated to say goodbye. Yet, this is the finale for the “[CMU MISM-BIDA] Attending Graduate School at CMU” series! After many things going on in my life, I had the chance to be back on Medium to write about my last semester as a Tartan, BIDA, and Heinzer. The pandemic is still ongoing at this point. In addition to achieving my master’s diploma, I also had the time to decide what I needed to do in my career. School is a lot the same, but what is different maybe what was on my mind:
IT’S TIME TO GET OUT OF SCHOOL!
I only had four standard lectures, most of them 12 units, and a PE class for the spring semester. I forgot to say this, but I must add this: I ALWAYS put easter eggs in my article. If you find one, feel free to tell me in the comments or send me a message on Instagram. Again, more details will be covered later in this article. If you want to see more of my day-to-day stories and posts, consider following my Instagram! My last article about my adventure can be found in the hyperlink: [CMU MISM-BIDA] Attending Graduate School at CMU in Fall 2021 (use wisely)
Carnegie Mellon University
Heinz College of Information Systems and Public Policy
Master of Information Systems Management — Business Intelligence and Data Analytics (MISM-BIDA)
Overview
The most challenging part of graduating is believing you have done it. All the job search and the tears may hurt sometimes, but hey, like I said: It’s about the journey. I have 24 units for electives in Spring 2022. Like always, I believe in the philosophy of learning as much as possible — — So there go another 2 CS courses. Again, this article will be simply about “graduate life” and will be posted in my publication: As a Graduate Student in Data. If you are interested in reading more about my graduate experience, feel free to check it out! I will go over my experience in the courses and life at Pittsburgh! You will, however, not see any internship-related parts in this article. (future articles to come!) Let’s get started!!
Stay tuned for the Pittsburgh food guide! (Last section)
Spring 2022 Class Schedule
BIDA has a requirement that is also a highlight of the program — The capstone project, worth 18 units. Since there are no physical classes for capstone, I had the opportunity to fill my schedule with all the best sections of each course.
Yes! No more 8 AM morning classes…
Advice: For future MISM students, as students in their last semester have priority in course selections, I would recommend taking the hardest-to-register classes (Not the hardest class). Last semester should be all well planned. Yet, the expected NN4NLP by professor Neubig was not available. For NLP, I made a change and took MLTGM instead. In addition, I took another course called ML in Production to learn more about productionizing ML from an SDE perspective.
The following are the courses that are on my schedule:
- 11–641 Machine Learning for Text and Graph-Based Mining: 12 credits (Full Semester)
- 17–645 Machine Learning in Production: 12 credits (Full Semester)
- 69-151 Intro to Yoga: 0 credits (Mini 3)
- 95–702 Distributed Systems for Information Systems Management: 12 credits (Full Semester)
- 95–720 Information Systems Project: 18 credits (Full Semester)
11–641 Machine Learning for Text and Graph-Based Mining
I was fascinated with the buzzwords of NLP and text mining until I discovered that there are also NLU, ASR, etc.
Sometimes reality runs over what you have planned ahead of time. I would have to be honest about this because I anticipated taking 11–747 Neural Networks for NLP (NN4NLP) this semester. Having taken many courses in DL, ML, and so forth, I thought it would be nice to add NLP/text mining to my skillset, which is why I decided to take this course. Before hitting the course registration button. I had several options regarding different NLP (or should I reiterate as language) classes at the LTI. Since NN4NLP is out of the picture, I was choosing between 3 other options:
- 11–711 Natural Language Processing
- 11–741 Machine Learning for Text and Graph-Based Mining
- 11–737 Multilingual Natural Language Processing
If I had more credits, I would have taken all of them. After going through an eight-month job search, I felt that I am still at the door of NLP rather than an expert in NLP. The courses at CMU mostly give you everything at once in a short timeframe rather than allowing you to understand and move on thoroughly. Most of that process includes going back to lecture slides, understanding notes, and comprehending the knowledge. At least, this is what I did for my interviews.
Back to the course! I think 11–641/11–741 is well structured, with many topics covered in the information retrieval field. Assignments started from PageRank, collaborative filtering to deep learning, and SGD. It is in Python, of course. The fun part about assignments is that it has leaderboards similar to Kaggle competitions. For instance, the collaborative filtering homework ranks students based on RMSE. You will have to pass a threshold to get all 10/10 points.
2018 Google BERT -> 2019 CMU XLNet
The course is like a walk-through of all the research papers over the years. In particular, the parts where professor Yiming Yang talks about the revolution of different word embedding techniques were the most intriguing. I love when she says: “This is from one of my students in 2019….” From the era of Word2vec to Context2vec, MLTGM covers these NLP topics but also the history. Below are the topics covered:
- High-dimensional Vector Spaces and Scalable Algorithms
- Link Analysis
- Neural Networks for Contextualized Representation Learning from Text
- Matrix Factorization
- Collaborative Filtering
- Extreme-scale Text Classification
- Graph-based Learning
Another highlight of this course is the interaction. Professor Yang likes students to speak out and ask questions. This may be somewhat scary for an introvert, but the more discussions, the better right? My overall thought on this course is that if you have 0 knowledge of ML, don’t take this course. However, if you have 0 knowledge of NLP, it should be fine to try this course.
17–645 Machine Learning in Production
One of the 1st courses in Machine Learning Engineering
My love of Spring 2022. The course has just a great mix of concept and practice. And has a lot of what I have been working on right now: MLOps, CI/CD, unit testing, etc. With the lectures being primarily on concepts and recitations on tools, students get to learn from the engineering mindset and apply it in the course project:
Some tools covered are:
- Git
- Apache Kafka
- Jenkins
- Docker
- Prometheus
- Grafana
I also thank the staff members for designing such a good course. The course is well-structured so that students are assigned to teams based on their experience in data science or software engineering. In the project, some team members worked on the backend, while others (such as myself) worked on building recommendation models. In the last lecture, each team will be able to see their performance in different criteria of ML in production.
The lecture materials are posted on GitHub, so if you want to take a look, feel free to look into the link below: (S22 Version)
69–151 Intro to Yoga
Who doesn’t like PE classes?
In my last semester, I decided to take not just academic classes but also physical education classes. I had a few on my list: Tennis, Soccer, etc. But since the vacancies got filled very quickly, I only got to take the yoga class. Not bad for an old bone like me? Most students were undergrads, but I had time to nap while doing the supported fish pose, which significantly helped with my body pain. Not much I can share about the course, but the instructor was professional and gave students a variety of yoga moves. The grading criterion was a pass or no pass. And of course: I passed! Recommend those who want to work out but are too lazy. You don’t even have to bring a yoga mat or brick. Just attend the course yourself and relax!
95–702 Distributed Systems for Information Systems Management
Extension of Java OOP
Distributed systems course is led by three professors: Mike McCarthy, Joe Mertz, and Marty Barrett. Yes! Marty again! In this course, you can build applications with a front-end web interface and some back-end components. Tools and concepts covered:
- Java (Obviously)
- HTTP
- Apache TomEE
- Jakarta EE
- Docker
- Heroku
- RMI
- REST API
- Android
- Apache Spark
- JMS
This course includes five projects, 11 labs, and at least 14 quizzes. It is a Java-loaded course, so I suggest brushing up on Java before taking it. By the way, Java OOP is also a prerequisite. This year’s lab format had checkpoints in each lab and required students to go to their assigned TAs to verify that they did the lab correctly.
Though the course is challenging in some ways, I still like how projects give you the flexibility to have your design. For instance, you could carve out the layout or design some easter eggs in your Andriod application. In one of the projects, I built an Andriod application that displays tourist information to users via REST API. I called it the AndroidInterestingCountry App! The easter egg is when a user searches for Wakanda. (See below)
Overall, the course gives you a glimpse of the standard principle and theory of distributed systems. One suggestion I would have for this course is to add more cloud components. I once asked an alum working in tech, and she told me that she wished there were more cloud computing components in the course. The lacking of this was a downside since most companies now utilize cloud resources for speed and efficiency. (Who does not know AWS, Azure, or GCP?) If you are a CMU student, you could also take the 15–319/619 Cloud Computing course from the SCS department.
95–720 Information Systems Project
The Application of Coursework to Real-world Scenarios?!
Heinz is a program that prioritizes sending top talents to the industry. In this scenario, there should be an industry-facing course. The capstone project is this course. 18 credits in total! BIDA students spend time with clients and try to solve analytical problems for them. Some of the highlights of each capstone project are:
- Led by a Heinz College faculty member with subject matter expertise.
- Teams of 4–6 talented masters’ students.
- Projects last 16 weeks.
So what do students work on? For MISM track students, you would have the opportunity to pick some areas of your choice (analytics, software engineering, consulting, etc.) But if you are a BIDA student, the default is analytics. You would not be able to choose the company you will be working with since it depends on which company sponsors each semester. Here are some of the partner companies that sponsored in Spring 2022:
- Bayer
- Capitol One
- Chubb
- CPacket Networks
- Honda
- PayPal
- Santander Bank
For my capstone experience, I would say it did not go as smoothly as I thought. Usually, you will have six teammates, but my team ended up with four as two others took a leave of absence. To work on an analytical project, you will need some data. The legal procedure took a long while, so we received the required data 1 week after our mid-term exam. With limited time, the team tried our best to get our hands dirty with the data and produce a result. Sadly, I wish we could have more time to thoroughly utilize what we learned at school.
Regardlessly, if your company is interested in becoming a capstone sponsor and working with Heinz talent, you can click the link below for more information.
Pittsburgh Life
So the Pittsburgh life part is back again, and I guess this may be the finale. And as usual, I will leave you with all the pictures! If you want more on Pittsburgh life, feel free to check out and follow my Instagram. (Lots of posts and stories)
Next: Seattle Life
CMU: The Cut
CMU: CFA Lawn
CMU: The Mall
CMU: Jared L. Cohon University Center
CMU: The Mellon Institute of Industrial Research
Heinz College
2022 CMU Spring Carnival
Commencement 2022
Snow Day Pittsburgh
PPG Paints Arena
Carnegie Museum of Natural History/Carnegie Museum of Art
Schenley Park
Frick Park
Arsenal Bowl
North Park
Duck Hollow Trail
Must-try Food!!!
Food is everything to me! If you are a foodie, feel free to follow me on Instagram. I constantly update stories on food and my daily life.
Noodlehead
Nak Won Garden
Senyai Thai Kitchen
Taiwanese Bistro Cafe 33
Everyday Noodles
Two Sisters Vietnamese Restaurant
Kiku Japanese Restaurant
Monterey Bay Fish Grotto
Epilogue
Time flies!
It has been like forever, but it ended so fast. I would conclude this year as finally getting ready to graduate. There have been a lot of projects that I worked on at CMU, but it is still different from working in an industry setting. One example may be that teammates will always show up while students may get sloppy. I had several lousy teammates along the way, but that is fine. Life is a rollercoaster ride, and after all that, I said to myself:
Why not enjoy the journey?
My 3rd and last official semester at CMU has been GRADUATING! This is the last of the “[CMU MISM-BIDA] Attending Graduate School at CMU” series. Thanks for joining on the ride, as I won’t dive into more of my school life at CMU next time. If you have learned something or have had a similar experience, feel free to comment below! Contact me via LinkedIn, Instagram, or Twitter if you have more to discuss. Also, feel free to follow me on Medium for more graduate life articles to come!
Previous Blogs (Let me keep it as 5s)
- [CMU MISM-BIDA] Attending Graduate School at CMU in Fall 2021
- [CMU MISM-BIDA] Attending Graduate School at CMU in Spring 2021
- [CMU MISM-BIDA] Attending Graduate School at CMU in Fall 2020
- Seal the Containerized ML Deal With Podman
- 6 Questions Answered at CMU’s Esports Industry Night
