Curious about the Georgia Tech Online MS in Analytics?
Originally published on LinkedIn June 8, 2021. This has been updated and edited with additional reflections since then.
Are you GTOMSA-curious? Since writing some GTOMSA course reviews, I’ve gotten a lot of questions about the Georgia Tech Online Masters in Analytics (GTOMSA) program. I wanted to compile all of the resources that I’ve collected about the program and answer some FAQs that people have asked me!
This blog was original created in June 2021 but has been updated here with my additional reflections after graduating! Apologies for the mixed tenses since some of this was written before I graduated, and some after!
FAQs
Why did you pursue the program?
When I moved to Atlanta from Chicago, I left my “business analyst” role (where I was doing data analytics) and accepted a “business systems analyst” contract role (where I was more like a product owner for an ETL pipeline). I thought to myself “how do I signal to employers that I want to do data analytics, and not a translating business requirements into user stories analyst role?” so I applied to the GTOMSA. I went to GT undergrad and had friends in the program, so I already knew the rigor, reputation, and quality of the program. Having “incoming GTOMSA student” on my resume helped me land great interviews when my contract was over, and I landed a great role in data analytics!
To be honest, I did not do research and compare this program to other programs, because the GTOMSA was cheap, a friend recommended it to me, and I knew that I could just take a class or two and drop out once I landed in a job that I liked. Well, I got into a job I liked with just “incoming student” on my resume, but I decided to take a class anyway. I enjoyed the class, and could apply it to my job, so I just kept taking classes, and suddenly, I was almost done!
I am so happy with my decision. I don’t think you could find another data masters program that you can do for ~$12k (more than half of which was paid for by my employers!). I have also learned so much that I have applied to my work, met some amazing friends, and really enjoyed my time in the program.
Has it helped your career?
Absolutely! I barely knew R or Python before the program, and since then I used R for a coding interview and I used python to create a store clustering model at work. I have expanded my understanding and confidence in modeling, statistics, and data. I helped a team member implement argolite to map out our database relationships — a tool I never would have known about without this program. I understand business more at a high level from my MGT classes. Hiring managers have told me that the GTOMSA on my resume helped me stand out as a candidate and I get more recruiter messages on LinkedIn. And I’ve met great people on the GTOMSA slack channel that have referred me to roles and that I have referred to roles!
The things that I learned, the community that I’ve built, and the name recognition of the program have all helped my career.
I’m trying to change careers. Is this program helpful? Is there anything this program doesn’t teach that you need to be a data analyst?
The one thing that you need to know to get into analytics is SQL, and it is not taught very much in the program. If you’re trying switching careers into analytics, it would be worth also getting a certification or taking a class in SQL before or in addition to this program.
I think this program does an amazing job of exposing you to analytics tools, analytics strategy, business questions you can answer with data, and more. There is some of the program that is more theoretical, but a ton of the program is around cases and business problems that show you how you can apply these ideas directly to almost any company. It’s one of the more applied programs that I’ve seen.
I think this program is a great way to get exposed to the data and analytics space, but it’s not a golden ticket to a high level data science role by any means. Pairing this program with some work experience (is there any analytics you can do in your current role?) and/or being willing to take a step down from you current position to slide into data analytics is probably the best way to get in the door.
Additionally, on the GTOMSA slack space, there is a #jobs channel and a #jobs_resume-review channel where current and past students help each other find roles in the analytics space.
Also, if you’re still not sure, or not sure that you want to complete the full program, there is the Analytics: Essential Tools and Methods MicroMasters which includes the first 3 classes in the program. It includes all of the same lectures, homeworks, and exams as the GTOMSA, but there is no need to apply to it, and if you complete all 3 you get a “micro masters”! If you decide to continue with the full program, it is very likely these credits transfer, but confirm with the GTOMSA advisors to be sure.
It’s been a while since I’ve done calculus, linear algebra, or coding. Will I be prepared to take these classes?
I think as long as you’ve seen integrals, derivatives and matrix algebra before, and have coded proficiently in one language (SQL does not count) at some point in your life, you should be okay. Most courses are pretty self-contained and will do a math refresh or link to resources that can read through to learn enough to get by. And for coding, googling and the O’Reilly books will definitely get you through if you understand the concepts. If you’ve never coded or seen calculus or linear algebra, it might be worth doing a crash course before starting the program.
How are the classes taught? How is homework assigned and graded?
Most classes are structured as follows:
- 1–3 hours of recorded lectures that are released every week that you can watch any time
- 1–2 (optional) live office ours per week hosted by TAs or professors, which are recorded so you can watch them later
- A homework assignment due every 1–2 weeks. This is either autograded, peer graded (in which case, you have to grade 3 of your classmate’s homeworks to get credit for yours), or graded by TAs depending on the assignment or class.
- 2–3 exams which are almost always multiple choice or coding autograded. I had a few coding exams that were graded by TAs, but not many
- A Piazza channel to ask questions and get help from classmates, TAs, and professors a-sync
You can do the work totally async, and relatively at your own pace. You can’t do all of the work in the first few weeks, or go on a month cruise without internet half way through the semester because there are typically deadlines every 1–2 weeks, and the professors don’t release content early, but you will always have at least a week to complete any assignment.
How do you balance work and school?
I make sure to only take 1–2 classes a semester, and balance my workload based on the “matrix” laying out how many expected hours per week the courses should take. Each class is represented in the row and column names, and the cells are how many hours per week you should expect to spend if you take the corresponding two classes. The middle diagonal is how long the class would take by itself.
I try to watch lectures for 2–4 hours during the week and block off 1 weekend day to finish lectures and do the homeworks. I also find having a study group that meets weekly (either in person or virtually) helps a lot when it comes to getting unstuck on the coding homeworks, and helps review lecture material for the conceptual multiple choice homeworks. It’s also just fun to have friends in your classes!
Lastly, I make sure to take off 1 day of work on exam weeks. This is helpful for extra time to study, to actually take the test, or just to give myself a break from studying so hard! Each class usually has 2–3 exams, so this can add up, but it is the best way to prevent burnout.
Remember — these classes are designed for working people. Each homework has at least a week to work on it. Most classes with weekly homeworks allow 2 drops. Most exams give can be started anytime during a one-week window. If you can magically find 4 hours a week to watch TV and drink wine when Bachelor in Paradise starts, it shouldn’t be too much harder to find 8 hours a week to take a class (but you may have to give up BIP).
How long is the program taking you?
I started Fall 2019, and I will finished Spring 2022, so in total it will take me almost 3 years or 8 semesters
What’s been your favorite class so far?
While taking the class, I told everyone and their mom that Data and Visual Analytics was the worst class in the world, but now that it’s over, I’m glad I have a poster presentation that I can show off to people, and it really is the class that teaches you how to do a project from start to finish, how to work on an analytics team, and how to embrace new and changing tools in analytics to get the job done. I think Data Analysis for Continuous Improvement was the most fun class I’ve taken, I still think about it every time I go into my closet or make a smoothie, but it was also the easiest course the program.
What track do you recommend?
The tracks are only 2 classes different from each other. Don’t worry about that yet. Take a few classes, figure out what you’re interested in, and then decide!
I personally did the Business track for a few reasons:
- The Continuous Improvement in Data Analytics class gives you a Lean Six Sigma Yellow Belt Certification if you get an A on your final project
- I am more interested in the business side than the ML side of analytics
- I heard that the business track was easier, and since I was already doing work in the analytics space, I wanted to finish the program faster
What are the pros/cons to an online masters compared to an in-person Masters?
Pros:
- Cost — The whole program can be done for <$12,000! Also, many employers will pay for some or all of your education, so check with your company to see if you can do it for free!
- Flexibility — lectures are prerecorded, so you don’t have to be at a specific place at a specific time. It’s great for people who work, travel, or don’t live close to a university.
- Student Diversity — there are students from all over the country and the world! There are students from 18–80 years old! You will meet some really incredible people
Cons:
- Networking — You don’t really get face-time with professors (although some professors do go to the live office hours), and it’s hard to meet other students. There is a GTOMSA slack channel, and every class has a piazza board, so you definitely can build a network, but it takes more effort than an in-person program
- It’s easy to get behind — and it’s hard to motivate yourself. When you don’t have a relationship with the professor, or friends in the class to help motivate you, it’s easy to skip a homework or fall behind on recorded lectures
Any other tips?
Keep in mind while reading anything about this program (including this blog) to take every review with a grain of salt. This program has incredibly diverse backgrounds — you have people from all over the world in these classes; ages 18–80; people who are already data scientists to people who have no STEM background and are trying to make a career change; people working full time, stay at home parents, and people taking classes full time. Something someone struggles with in this program may come easy for you and vice versa due to different backgrounds and experiences.
Official and Unofficial Program Resources
- Degree Overview — how GT presents the program, and all of the official information
- The Curriculum — this includes all classes in the program, along with a breakdown of track requirements. Note: Not all classes that are listed here are ready for the online program. They will eventually have online version for all of the classes listed, but many statistics electives are not available yet.
- The Micromasters — The first 3 classes in the program are available to take by anyone! They’re the same classes — same professors, same lectures, same homeworks, same exams, same timelines. Currently, the credits do transfer if you apply to the MS program, but the advisors have warned that they’re unsure if this will continue forever, so ask an advisor in the program first. If you complete all 3 classes, you will receive a micromasters in analytics!
- Course Reviews — Curious about what people think about the classes? Check out the reviews!
- omsa.ga — the student compiled GTOMSA survival guide. It has information about the student slack, details on courses (language; difficultly; old syllabuses), costs, useful links, the matrix (see FAQs below for more info), and more
Other Program and Course Reviews:
- Georgia Tech’s MS Analytics Program: My Review — The Data Generalist
- Georgia Tech’s MS Analytics Program: My Review Part II — The Data Generalist
- How to Graduate Georgia Tech’s OMS Program in 1.5 Years
- Georgia Tech Online Master of Science in Analytics (OMSA) Review
I think reddit is a treasure trove of information. Search on /r/omsa for questions you might have (especially around admission) — I’m sure someone else has asked it before! These two posts specifically stuck out to me:
- A post attacking the quality of the program: r/OMSA — ISYE 6501 indicative of program quality?
- A reply to critics of OMSA: r/OMSA — reply to critics of OMSA . The top comment rings true to me:
What it comes down to is that GT teaches very differently than other schools. At GT, they throw you in the fire and expect you to teach yourself how to get out of it. At every other school I’ve attended (including some of the best in the world), they teach incrementally and each lesson builds on the previous. At GT, they just assign the final solution and expect you to teach yourself.
The GT method of being self-taught is very powerful, but very frustrating. If you’re not used to that method or adapt to it, you’ll likely be very unhappy with the lack of instruction and be unsuccessful.
Such a program graduates excellent data scientists, but will also have a high drop out rate.
I hope having all of these resources in one place is helpful, and helps some make an informed decision about pursuing or not pursuing a Masters in Analytics Online at Georgia Tech. As always, feel free to reach out or drop questions in the comments!
Go Jackets! Sting ‘em! And THWg!