My OMSCS experience was rewarding, but I think I echo most other commenters when I say it is entirely dependent on how much effort you can put in. Personally, I graduated in May 2017 after 2 years of study (worked full-time during those years), with a decently high GPA and a good understanding of the basics. As my undergraduate degree was in Mechanical Engineering/Math, it was interesting to get more involved with machine learning/robotics from the software side. If you already have CS experience, I don't know how much this would be beneficial over more traditional on-the-job training, but for someone who is diversifying/changing specialities, it was very useful. Though in my current role, its mostly used as a filter, so all the hard problems that encompass both departments seem to end up at my desk...
Additionally, one of things about OMSCS vs a MOOC or self study is that because you have invested financially, you are more motivated to succeed. This can be especially useful if you are maintaining a full-time job while attending, as getting home from work to do nightly programming can be a challenge some days.
Do you think it would be possible for an Information Systems major that isn't phenomenal at math to succeed in this program?
I took a couple of incredibly basic programming classes, a decent class on web development, and discrete math. However, I didn't do any higher-level programming, calculus, or an algorithms class. I'm not sure if I would be able to jump right in or not.
Graduate level algorithms is a required course. Many of the courses in the Machine Learning and Artificial Intelligence tracks are very math intensive.
"Isn't phenomenal" is hard to qualify. It's kind of relative to what you consider phenomemal.
I've always done well academically relative to my peers. Most of the courses are on some kind of curve. So I've done fine in OMSCS.
I guess what I'm getting at is...if you've done good enough academically in the past and you're willing to apply your full effort, you'll likely do well at OMCS.
