How to Graduate Georgia Tech’s OMS Program in 1.5 Years
The Georgia Tech Online Master of Science (GT OMS) program is becoming more popular to data enthusiasts around the world. An affordable program from a well respected university that can bend to any student’s schedule is a dream come true.
I recently graduated from the program in a year and a half (5 semesters total). When I was accepted to the program, I did a lot of searching on the web for reviews of the program with very little success. Once I was choosing classes, I once again struggled to find background information on a lot of the courses I wanted to participate in. Was it a tough class? What would I learn? Is the coursework load big or small?
I wanted to put together an article giving a review of the program as well as a timeline of what courses I took to complete my degree. I always tried to line it up that I would give myself an “easier” course load class and then one course that would require most of my attention.
Program Overview
The Georgia Tech OMS program is a 100% online master’s program specializing in analytics. This is not a computer science master’s degree. The official term is “Masters of Science: Analytics”. It comes from their school of engineering. There are a few different “paths” that you can take, requiring different courses to complete. I took the Business Analytics track mostly because of what was available during the semesters I was taking classes to complete the program quickly, not so much about what I wanted to truly study.
All of the courses have video lectures that can be viewed at any time. Most classes had a weekly meeting time (also recorded and posted online) students could attend to ask the professor or teacher’s assistant any questions about homework / lectures / exams. Exams were done using a program called Protortrack that would record you and your computer screen while you take your exam. Some exams were open notes, some were closed book, it all depends on the professor.
You’ll see a few of these semesters I took three courses which seems a lot for an online master’s program. Now, I’m a natural nerd. In my free time I am coding my own projects, so taking on more coding work was not that big of a deal for me. I probably would spend 10–20 hours a week on the courses, 2 or 3 hours a day during the week and then about 4 hours each day on the weekends.
Spring 2019 Semester
CSE- 6040: Computing for Data Analytics
If you have any experience in Python, you will enjoy this class. If you don’t, this one might be one of your tougher courses. It is one of the core courses you have to take to graduate, so don’t try to find a way around it. This class focuses on using Python to solve different computer science questions relating to things about text scraping, SQL in data frames, data manipulation, and computing optimization. The homework assignments were done in Jupyter Notebooks that you needed to complete (it also did the grading in the notebook which was really nice). The exams were also done in those Jupyter Notebooks and were open book as well. You had 24 hours to complete the exam once you started. I was very comfortable in Python before I took this class, so it was easy early on but gave me a run for my money towards the end when it came to optimizing code.
Overall: Good course that solves some fun questions using Python. Can end up spending a good amount of time on the homework and exams, but nothing that I lost sleep over.
ISYE-6501: Intro To Analytics Modeling
One of my favorite courses in the whole program. This course does a great job giving different problems that can be solved with machine learning problems, both simple and complex, using R. The machine learning solutions never went too deep into the functionality, but more gave a good understanding of how they worked and how they could be applied to different problems. I got to learn about simulations in this course that inspired me to take the simulation course later on in the year.
One thing to look out for in this course and in other courses: other students grade your homework. This actually posed more of a problem with every course I took that had student grading. You will have to endure students who grade too harshly and then talk about the “high standards” they carry. I even had a teacher have to step in and send a message to the rest of the class to be more respectful of people’s work. This was a class that once or twice I got good grades on homeworks and then other times I would get a lower grade because of a tough student grader.
Overall: This course does a great job introducing you to machine learning algorithms that you already know about and some new ones you will get to experience. The teaching is great, the lectures are appropriate length, and the work wasn’t too difficult. Beware of the student graders, especially if you’re taking this class early on like I did. Don’t let them discourage you.
Summer 2019 Semester
Warning on the summer classes. You would think that since all of the program is online that all courses will be available during the summer as well. This was not the case. The main reason I took Digital Marketing was because the other classes offered didn’t interest me or didn’t line up with any of the three tracks required to graduate. By selecting Digital Marketing, I had to commit to the Business track.
MGT 6311: Digital Marketing
This was a course that I actually don’t remember coding very much, if not at all. I might have done some simple calculations for homework problems but nothing too in depth. I did not have a lot of background in the marketing space so it was a good class to understand how ideas are made, what specific components of a campaign are called, and how analytics could come into play to make better decision making. The lectures were pretty long (but you can speed up the videos) and there was a lot of reading. I would highly recommend to anyone who will be working with marketing data in the near future.
Overview: Lots of reading, listening to lectures, and writing for homework but a class that gave me a lot of context and insight about digital marketing. This is especially important for the world we live in today.
ISYE 6644: Simulation and Modeling
Another class that I really enjoyed due to the topic and the teacher. Dr. Goldsman was one of the professors that I enjoyed the most because he explained things well and did it with a joke. Fair warning: this class really focused on advanced mathematics. I’m talking about integrals and other high level calculus. If you’ve never experienced that kind of math before, this class might not be the one for you. If you have taken advanced calculous classes in the past but need a refresher, you will be fine. Dr. Goldsman walks through a bunch of examples and if you have the homework open while you’re watching the lectures, you will be able to piece them together pretty easily.
The actual course itself wasn’t what I expected in both a good way and a bad way. I was able to learn about a lot of the math components of simulations, but I didn’t really ever program anything. It was a math class, not a programming class. We did use a software called Arena that showed how to create simulations that I could see being extremely important for jobs that would use simulation on a daily basis, but I was hoping to learn how to create simulation programs in R or Python.
Overview: If you enjoy math and want a good, fun course to take, simulation is a perfect choice for you. If you are more about programming and don’t really care much for the math side of things, this might not be the best choice.
Fall 2019 Semester
This was the semester I decided to ramp it up a bit. In terms of work load, this semester had me working a lot more than I originally thought I would due to Bayesian and Data & Visual Analytics. If I had to do it over again, I might have tried to put in another class with less work load switched out for one of these two.
ISYE 6240: Bayesian Statistics
I had taken deep mathematics courses before the GT OMS program, so I was very excited to learn about Bayesian Statistics. After the first few weeks, I was actually nervous I might need to drop the class since I was struggling to understand the material. It seemed like some of my classmates felt the same way. However, after pushing through it I really started to figure out how everything worked together and ended up enjoying the class. This was another class that had high level mathematics and statistics, so if you’re not familiar with Bayes theories, I might avoid this class. Have to do an individual project at the end, but the exams were given as PDF’s that needed to be completed in a week.
Overview: Class is very difficult at first but ended up really liking it in the end. One issue I didn’t like was the programming used. It wasn’t done in R or Python but done in a statistical language called WinBUGS that took me a while to figure out as well.
MGT 6203: Data Analytics in Business
This class was a slower pace and an easy walk through of how data analytics can be used in business (hence, the title). The lectures were easy and the homeworks could be done quickly if you follow along with the course notes. Not too much to say about this class other than make sure you take it with a course where you think you might have a lot on your plate.
Overview: Class that walks through fundamental analytics to solve things like logistic regression, interpreting models, and some business questions that can be solved with analytics. Light coursework, so a great class to match up with a class that will require more attention.
CSE 6242: Data & Visual Analytics
This was the class that I had to spend the most amount of time and effort in. It is a required class for any of the paths, so there’s no avoiding it. The title of the class sounds easy, but this is one of the toughest classes because you use a lot of different languages. The homeworks are really more like projects. You work in Python, D3 (a form of JavaScript), Tableau, Azure, Pig, and other technology programs. You work with small and large datasets, and then one final project that you work with other students for a few weeks.
I wish I had been more understanding with how much work happens in this class. I probably spent at least 15–20 hours a week just on this class alone. When you take this class, try to match it up with a lighter workload class.
Overview: Tons of work! Once you figure out how to solve the problems, you feel like a wizard but it takes a while to get there. Make sure you work well with your project mates so you can work together on helping solve the homework problems. You get a taste of everything a data scientist does, very little math, but lots of programming.
Spring 2020 Semester
ISYE 6414: Regression Analytics
This was a typical regression class for anyone who’s taken one before. It goes over the types of linear regression that everyone is familiar with (simple, multilinear, logistic, etc) but then also threw in some new wrinkles like poisson and exponential logistic regression. I didn’t really want to take this course since I had taken one in my undergraduate studies but this was one that qualified me to graduate. I struggled on some of the exams since they weren’t so much about interpreting outputs of regression models and more about different assumptions that must be made about models. All of the coding is done in R.
Overview: Class that didn’t require a lot of time and effort, but worth taking for anyone who doesn’t know the fundamentals of linear regression models. If you’re wanting to be a data scientist, this should be one of the top classes on your list.
MGT 8803: Business Fundamentals for Analytics
This was the class that I enjoyed the least. The homeworks were simple but the lectures were extremely long and dry. The exams were very long and mostly about things discussed in the lectures and readings, so I felt like the whole class was just memorizing things in lectures and not so much about learning new things. The lectures were about things like accounting, time value of money, digital marketing, and other topics about businesses. There were some group projects, but no actual coding of any kind.
Overview: I didn’t really like the class. I felt like it was just an overview of different facets of a business, but nothing much about analytics or programming. Unless you want to learn more about how a business is run than about analytics and programming, this class probably isn’t the one for you.
MGT 8813: Financial Modeling
I was a lot more excited about this class going into it and then found myself to be disappointed at the depth of the lectures. This class should actually be renamed to “Completing Financial Documents using Excel”. The first few weeks are just about learning financial documents and filling in the missing pieces, and the last few weeks are learning how to compare different companies to each other based on their financial documents. I understand this is the fundamentals of comparing businesses to make smarter decision making, but I thought I would have done something a little more complex like Monte Carlo simulation or other machine learning models.
Overview: Class sounds super interesting but it isn’t. This was one of the lightest workload classes to take but I didn’t find the class helpful in advancing my skillset or understanding of businesses or analytics. If you’re new to the space, this would be a good intro class. If you’re expecting something more in depth, look somewhere else.
Summer 2020 Semester
MGT 6748: Summer Practicum
The summer practicum can be done either through your employer or through GT. They have programs that work with the school to give students projects they can work on, but I was able to do it through my employer. All that is due is a midterm PowerPoint to talk about what you’re working on / what you’ve completed / what you need to complete, and then a final paper. They also have some videos to watch about leadership traits and how to present analytics to non-technical stakeholders.
Final Thoughts
I was really happy I decided to take the GT OMS program. Given the options of online programs, this one was the same standard of high quality with a much more affordable price. Was I a little unhappy with some of the classes I had to take? Sure, but who has ever had the chance to get everything that they want?
This program will challenge you at times. This program will tell you things you already knew and will bring new light to new ideas that will make you a better analyst. This program takes the high level topics of data analysis and data science and presents it to you in a way that will make you more valuable to your business and will help you problem solve in your career.
If you’re looking for a masters program in the data sector, the Georgia Tech OMS program should be at the top of your list.
