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Georgia Tech Offers Online Master of Science in Analytics Degree for Under $10K (gatech.edu)
533 points by dgritsko on Jan 12, 2017 | hide | past | favorite | 258 comments



As someone who completed a (on-campus) CS masters at GT, I really wish I didn't. The classes were of very poor quality - it was clear that they were a low priority for most faculty. Andrew Ng's Coursera class on Machine Learning was the pedagogical highlight of my time at GT, and I did it on my own initiative (and it's free).

I know people have many reasons to get a Masters. If your goal is to take some higher-level classes, you can do better than GT. If you are self-motivated enough to do an online degree, you can do it for free. Aside from free offerings from sites like Coursera, you can find whole courses up from many institutions - with syllabi, lecture slides, homework assignments, etc.

If you're planning to do it for the salary, in my experience the degree ended up being worth a $95K to $115K bump in starting salary. Compare this with the 2 years of industry salary that I would have received, and the 2 years of experience (and raises that come with that). I know I wasn't paid better than the folks who had been with the company for 2 years more than me.

If you're thinking about it for the sake of your resume, I do hiring screening / interviews now (for Data Science and Software Engineering positions) - and I really don't care if the applicant has an MS or not (or what classes they may have taken). Most folks I know that do hiring think similarly. My main signal from your resume is projects you've been on and how you contributed.

From my point of view, this program is a losing proposition for any potential student.


I just graduated from the OMSCS (online master of science in computer science) program, and I found it a wholly worthwhile experience. It was challenging, informative, and for the most part well-run. Software Analysis and Test in particular was a real eye-opener. And while Computability, Complexity, and Algorithms was a hideous death march of terror, the material they covered was some of the most interesting I've ever experienced.

Yes, you can study the same material on your own, but you won't earn a degree from it. Now that I've got the degree, I'm in much better shape to pursue further learning on my own.

Note, however, that I didn't do this to improve my resume, go fishing for a new job, or try to get a raise. With tuition reimbursement from my company I only spent $3500 over 2 1/2 years to earn a full-fledged master's degree.

Based on the above, I can't agree that it's a losing proposition.


"Now that I've got the degree, I'm in much better shape to pursue further learning on my own."

Could you explain a bit more what do you mean with this statement? Is it that you feel better prepared to study advanced topics (like advanced ML/Data Science) or was the degree a requirement for something else you wanted to pursue?

I'm curious about what other "doors" having this degree opens, other than the bump in salary mentioned by others.

Congrats for completing the program btw.


I was exposed to new sources of information throughout the program, such as Youtube videos, books, and lots of papers on computer science topics. Being required to read all that upped my ability to absorb and comprehend them. So now I feel I can go back to, say, my algorithms books and do a much deeper dive into topics not covered in depth. Or go follow up with some of the tools, like Korat or Dafny, and learn more about their internals and applications.

I honestly don't expect it to open any additional doors for me. I'm a software developer with 30 years experience and have been working for the same company for nearly 18 years. I wasn't looking for any changes, I just wanted to be better at what I did.

Thanks for the congratulations. It was quite difficult at times, took a lot of effort, but was totally worth it, IMHO.


I'm not the author of the above comment, but here is my take..

I think one benefit of a curated course is that it includes materials you didn't even know exists. We can easily improve on our known unknowns - just pick up a book or google it - but unknowns unknowns are... well difficult to learn. I think going through a graduate program helps you get a better grasp of what you don't know AND what you didn't know you didn't know.


Yes, that's certainly an aspect of it. As someone with a lot of professional experience, it's easy to get into a rut with what you're required to do in your day job. I always tried to keep up with new techniques, frameworks, etc. But getting the degree forced me to learn more about the course subjects. Like in Computer Networking, most of my low-level networking knowledge was several years old. Being exposed to Software Defined Networking was very interesting, and I enjoyed experimenting with Pyretic to explore how it works.


In my experience having a well structured program with good content is more important than it being an in person program. This is especially true if there are ways to reach out to live help when a student is struggling with some aspect of the program.


Absolutely. One of the key pillars in the program is student-to-student interaction, either via the Piazza course communication system, or direct contact.

I have extensive knowledge of VMs, so I helped many students get their environments set up. I could often diagnose show-stopping problems for the less-experienced students very quickly, since at my experience level I really have "seen it all". And if it wasn't something I could diagnose that way, I'd set up a Google Hangouts call and watch exactly what was happening on their screen and get them through it.

Many other students did the same thing. In Computability, Complexity, and Algorithms, there were some students who were apparently math robots from the future, solving the problem sets effortlessly, and posting them to Piazza so that the rest of us could use their work for study purposes.


Not OP, but I'm applying to some graduate programs this year that lead to a Ph.D. in CS, and some institutes have a hard requirement of a Masters degree for getting into their Ph.D. programs, while some (like most top US universities, including GATech) allow you to enroll with a Bachelor's Degree, provided you'll do the required coursework before the dissertation phase. It's really cool that one can earn a Master's Degree while working full-time, before applying to a Ph.D. program :)


How much time did you spend on coursework per week? Were you working full time while you did this program?


Yes, I worked full-time. I'm fortunate in that I WFH, so I could allocate the time I'd have had to commute to school, figure 90 minutes a day. I'm married but have no children, so I didn't have that requiring my attention. Then I'd augment with whatever additional time was needed (at the expense of World of Warcraft).

I'd figure for a "light" class that had a fair amount of coding or was in a subject area that I had considerable experience would be 10-15 hours a week.

A semester with 2 classes of moderate difficulty would be 20-30 hours a week, depending on homework pacing, amount of videos and readings to study, etc.

The hardest class I took was my last class in December called Computability, Complexity, and Algorithms (CCA) and at the end I was doing 35+ hours a week trying to get ahead. It was hugely difficult due to my very weak math background, but I somehow got the hang of it and passed with a decent "B" and graduated.


I did both my BSCS and MSCS at Georgia Tech. While I have many complaints about the school, the quality of the classes is not one of them, for either the undergrad or grad programs.

That said, with a couple of notable exceptions, the graduate classes are there for PhD students as first and second year background material so they have some starting points for their research. This naturally leads to a format where the semester can effectively be described as a long reading list of papers and lectures to spur discussion on the content of the paper. I was planning on pursuing a PhD when I started into my MS, so this format worked quite well for me at the time. In the years subsequent to that, the grounding from those classes has given me starting points for deep dives into problems I encountered at work[0].

It's interesting that you brought up machine learning. Charles Isbell's Intro ML class was a significant exception to the pattern I described above. In addition to high quality, pre-prepared lectures peppered with entertaining anecdotes, the had high quality projects that worked with pratcial tooling. It was also probably the highlight of my graduate career[1].

[0]: In particular, the material covered in my graduate systems classes has been invaluable for not reinventing the wheel for the thousandth time. The material from the couple compilers classes I took on a whim has been a huge boon when talking about software correctness. I work on the hypervisor underneath GCE. Correctness is near and dear to my heart, but performance is right there with it :)

[1]: For undergrad that dubious honor has to go to Olin Shivers, not only because of his eclectic teaching style, but also because his class completely altered the way I think about problems in computer science. In particular, my mindset shifted to one of models of computation and decomposition of problems into subproblems for which the simplest model could apply. I have an example I'd like to write up, but it's a bit long for a footnote.


Hi! I'm the director of Georgia Tech's MS in Analytics program (both on-campus and online).

GT's MS in Analytics degree is actually designed specifically for people who are going to go out and work in the analytics field -- it's not a pre-PhD degree, and our courses are targeted primarily at people who want to learn and apply analytics. We have an industry advisory board that helps us target course and program content, and we're constantly working to make sure our coursework is focused to the right cohort. We even have a required applied analytics practicum (both for on-campus and online students) where our students work on analytics projects for a wide range of companies and organizations.

Perhaps other degrees are different, but the MS Analytics is a very practice-focused degree.


I may be an educational purist, but to me I cringe when I hear universities boast about the "practicality" of their degrees they offer. You get a degree to prove you can learn. The courses should be heavy on theory and concepts. If you teach these well enough, ideally your students should be able to easily pick up whatever FOTM development stack or tool is out there and roll with it. I wish we could reverse this trend, but it just seems like it's too much good PR to say "hey everyone! come to our school and you are guaranteed to get a job!"


Certainly with the rise of sham/for-profit universities, sales pitches promoting 'practicality' now launch red flags, and deservedly so. But if the role of 'higher education' is to be a practical one (as engineering programs have always been), it only makes sense for schools to ask industry what it needs and then serve those ends, first and foremost.

In general, while theory has great value, it's more as a stepping stone to higher study than as an end unto itself. Few computing pros submit proofs among their deliverables. And devising the theta bound on a function or resolving the terms of a CSP simply don't deliver much value when working outside PhD-level R&D labs and writing peer-reviewed papers.

I believe there's a great deal of value in applied non-PhD track academic programs like GT's online discount offerings, especially in serving professionals and employers. I also believe it's high time that universities clued in to the unmet need that most of us post-academics face toward helping us continuously re-educate ourselves as we progress through our careers. Few of us pros can return to campuses, even part-time. Distance learning meets a crying need. And when done right and priced-right (as I believe GT does), I have nothing but kudos to offer in return. I say, more power to GT's authors, curators, and administrators who made this possible. And to all who make this greatly empowering service possible: thanks, and keep up the good work.


I disagree. The role of a university CS degree is to bridge the gap between high school student and software development professional. That's going to include some theory but a lot of hands-on experience with modern development tools. It should include a healthy amount of group work and tons of coding projects.

If you want to play around with theoretical computer science, get your PhD. College educations are too expensive to not be imminently practical.


I disagree with this sentiment based on my own experience. I did great in my BS CS program from a highly ranked program, but was woefully underprepared for industry and quite frankly a bad software engineer. Graduates from traditional programs often leave with next to no experience with testing, version control, team structure/process, newer languages, frameworks/3rd party packages, etc, and my experience in industry is that it's a role of the dice if your company, team, etc are interested in teaching you or waiting for you to learn. The only people I know who graduated with those skills are people who either had amazing mentors or were natural hackers in their spare time. If I could re-design my education, it would be 2-3 years of theory and then 1-2 years of applied liberal arts education before starting an actual career.


Graduates from traditional programs often leave with next to no experience with testing, version control, team structure/process, newer languages, frameworks/3rd party packages, etc, and my experience in industry is that it's a role of the dice if your company, team, etc are interested in teaching you or waiting for you to learn.

It's a waste of time to teach industry tools at a university. It's much more valuable to be taught fundamentals. Know your fundamentals well and any new tech will be much easier to learn. It's long-term thinking - put in the investment to make sure you can change skillsets in the future.

All the things you mentioned tend to be ephemeral and change a lot within a few years. Look at the git monoculture that's sprung up in the last 5 years for example - 10 years ago it might have been reasonable to teach SVN.


And if you learned SVN, you would have had a solid base for understanding GIT. Would you expect students to learn source code control in the abstract or not at all?

You have to do programming assignments anyway. Why wouldn't you require students to learn and use the latest source code control tools while they're doing their development?

Teach students to write tests, use source code control, utilize continuous integration, etc.

Although the specific tools, languages, and approaches will evolve in the coming years - none of the above are going away soon.


Git is a very complicated piece of software. it's not intuitive, it has a famously poor CLI, and it takes time to learn.

Time spent making undergraduates use git is time that could be spent teaching them long-term, fundamental skills.


vi isn't very intuitive either, but there's no better way to learn something difficult than to learn it when you're young. I've been using vi professionally for 30 years thanks to my early GT classes. It's probably the single-most valuable skill that I learned there that I still use today.


I'm a vi(m) user, but I have to say - it's not a fundamental part of computing at all. It's just a very popular tool. A lot of people don't know how to use it and manage to make amazing things.

there's no better way to learn something difficult than to learn it when you're young

Hmm, define 'young'. I'm in my late 20s and I find it easier to learn new things more than ever - including things I failed to learn in my teens and early 20s. Maybe I'm just a late bloomer, and it took me a while to "learn how to learn". But maybe I'm still young in the eyes of someone who has been using vi for 30 years (:


If you know Graph theory then you know git, all that remains is just reading the man page for specific commands. Intro to Graphs/Graph Theory is generally in the curriculum at all university compsci departments

Testing ect is usually covered in all intro classes (assert libraries) or industry type testing like JUnit by a software engineering elective typically taught in Java


If you know Graph theory then you know git, all that remains is just reading the man page for specific commands.

Just because one of gits key abstractions is based on a kind of graph, I don't think it follows that knowing graph theory means you know git. I mean LISP is based on a graph structure as well but plenty of people find that confusing.


Exactly, we were checking in Java assignments in the form of a ZIP file in 2009 that we had validated with print statements. It wouldn't have been that much more work to structure the algorithm assignments in that class in a way more similar to industry workflows even if the workflows are an evolving target.


Fair enough, and I should have been a bit clearer in my original post.

In my experience with the MSCS program (nearly ten years ago at this point) the core required classes were mostly well structured and would serve people well continuing onto a PhD or growing their skill set for industry. The core constituted a relatively small chunk of the overall credits required, though, and the elective courses tended to be more along the lines of what I described.

I'm glad to hear that the Analytics program has a more dedicated focus on practical matters. It might be interesting to produce a series of similar (but narrower) curricula that amount to curated collections of CS classes making up degrees in Machine Learning, Systems Programming, etc.

I personally really enjoyed my dartboard-oriented approach to class registration. I learned more than I've never needed to know about approximation algorithms, cryptographic theory, and compilers. Even if much of what I learned there hasn't proven itself directly useful yet, I really enjoyed learning it for learning's sake, and I think I'd have had a hard time picking up some of the gems I pulled out of that since. I also still have a hobby of proving problems NP-complete on demand as a bit of a parlor trick (within the limited scope of problems for which you can apply the small handful of patterns I've burned into my brain over the years :).


Can professional experience and a partially completed bachelor's degree in SE substitute for the undergraduate degree requirement?


I asked this question in a number of places a couple years ago and the answer is basically no.

I did, however, find that my undergraduate university had a great program for people with nearly complete degrees who had been away for a few years.

I'll be finishing undergrad this May and am now looking at grad schools. Feel free to contact me if you want to chat about this because it's been surprisingly hard to find info or advice in our situation.


https://www.udacity.com/georgia-tech/faq

Who can apply to the OMS CS degree program? Admission into the OMS CS program will require a Bachelor of Science degree in computer science from an accredited institution, or a related Bachelor of Science degree with a possible need to take and pass remedial courses. Georgia Tech will handle the degree admissions process. For more information please visit the Georgia Tech program page.


I got into analytics while using the quant investment site Quantopian.

Mostly you use python numpy and scipy to analyze a large time series data set (stock market) to predict pricing while having a low correlation to the overall market movement.

I had some success and won their 6 month contest, but I still feel like a bit of a hack. I'd like to move into the financial quantitative analysis industry.

Would you say this GT program would be a good stepping stone?


In some ways. There's a class called ML For Trading that's very fun and like an intro to computational trading. The professor runs a company in that space.


I'm very interested in this program.

What is the best way to get in touch with you and get the syllabus material for the courses?

I'm at rememberlenny at gmail.


Charles Isbell is still at GT? Holy cow. I think he was the teaching assistant when I was taking VAX assembly back in the late 80's when I was there. Seemed like a nice guy.

It's amazing how you don't think of someone for almost 30 years, but you read their name in a comment on HN and memories come flooding in. What do those neurons do while they're waiting to be used again?


He was a associate professor in the early 00's.


> I did both my BSCS and MSCS at Georgia Tech. While I have many complaints about the school, the quality of the classes is not one of them, for either the undergrad or grad programs.

I also did BS and MS at GT, and while I generally share your experiences there were 3 or 4 truly disappointing classes during my MS. They didn't ruin my overall experience, but I can see how someone could happen to have more experiences like those and fewer positive ones and come aware with a very different perception of course quality.

My overall opinion of GT is mixed, but rigor or the courses is not one of my top critiques.


I took Isbell's class as well, and perhaps here we can share our respective experiences.

In the year I did it, the class was structured as follows:

At the beginning of the semester, you'd pick two datasets.

Every two weeks, you'd apply two or so algorithms that were being covered at the time (maybe k-means and SVD, or a NN and SVM) to your chosen data sets. There would be a set of variations that you were supposed to apply to each algorithm. Typically you'd normalize or clean the data in some way. Perhaps you'd filter outliers, etc...

The result would be a set of experiments to run (2 datasets) x (2 algorithms) x (2^3 variations per algorithm). You would compile the results into a (10 page max) paper, with analysis about how the dimensions differed.

It was up to the student to figure out how to actually implement this pipeline (I used sqlite + numpy/scipy/scikitlearn, many used Matlab).

On paper, this sounds like a great class - what a wonderful way to learn about how different approaches relate to each other, and how crucial the process of preparing data is to the effectiveness of the algorithm. In practice, however, this did not happen for most students I knew.

These students spent most of their time finding implementations of the algorithms and hacking at them to actually run all the experiments. They then rushed through gluing the results together through some semblance of analysis. Alumni of the class I knew said the same thing about their experience.

This analysis was read by TA's. There were I think 3 of them for about 100 students. We wouldn't get the papers back for weeks (long past we moved on to new material). When we got our papers back there was very little feedback of the content - mostly it was noted that we submitted the work on time, and had successfully performed all the experiments required.

I agree that Isbell is a joy to listen to - he is charismatic, entertaining, and I too enjoyed his anecdotes. However, I felt like you would only get something out of his lectures if you already knew what you were talking about.

When I think about the quality of the class, I think about how responsive the class is to the individual needs and progress of the student.

If you say that it's up to the student what they get out of the class, and your bar for a good class is that the content is arranged in a nice manner, then here you go https://pe.gatech.edu/sites/pe.gatech.edu/files/agendas/CS-4... ... any self-directed student can grab Mitchell, and do the weekly assignments I describe above - all for free and in the comfort of their own home.


I agree that latency and detail of feedback is an enormous problem with this sort of partially-guided coursework. However, it's a generalized problem with higher education, not specific to GT, in that when implemented effectively it's one of the most valuable education experiences but difficult to scale, because it demands time-consuming supervision.

This is especially true of term project courses, where the final portion of the project to which you devote the most time and creativity is also the part for which you're likely to receive the least feedback.


>However, I felt like you would only get something out of his lectures if you already knew what you were talking about.

I disagree (having taken the course as an undergraduate and it being my first major exposure to machine learning). Certainly if all you do is attend the lectures, you're going to miss some background knowledge, but that is true of most (if not all) university courses. You're supposed to devote 2-3 hours of outside work for each hour of lecture. Meaning 6-9 hours of studying per week outside of those lectures.

Some of this is doing the projects, although some of it is personal investigation.

There are failings of his course (one of the biggest at this point is that it doesn't do any work with the state of the art now), but I think that the fact that his course caters toward people who are self-driven is not a failing.

The best way to look at what the goal of the course is is by looking at his exams. If they weren't different than you took them, they were intentionally too difficult for the allotted time, leading to low averages and incomplete work by the majority of students.

However, the course allows motivated students to make connections between concepts, with the help of the professor and the coursework. Having someone "leading you" down the right path is very helpful, much moreso than a textbook alone.

I really do think that there is one exam question that sums up Isbell's course perfectly: its the one where you are asked to compare and contrast 4-5 aspects of 4 randomized optimization algorithms (RHC, GA, SA, and MIMIC) and explain situations where you'd use each and why.

The course's goal is to lead to a strong intuition for the algorithms covered (sadly at the partial expense of a theoretical understanding), not everyone puts in the work to develop that understanding, but that's not a failure of the course, necessarily.


I do agree that having materials that provide an approach to a topic is very useful, but as I mention elsewhere such materials are available for free online.

You can find the syllabus for Isbell's class and follow along. You can do the readings and programming investigations. If you like lectures, you can find many full courses on YouTube (I found caltech's lectures https://www.youtube.com/watch?v=eHsErlPJWUU to be the best at presenting SVM's out there, although this was probably my third attempt at understanding them so maybe the other resources rubbed off.. they also skim over the quadratic programming detail but I get that this may be beyond the detail that many people desire in an intro class).

If you have to teach the material to yourself, how is your experience improved by being in the class?


>You can find the syllabus for Isbell's class and follow along

To be fair, most of Isbell's course (lectures) is also available on Udacity.

>If you have to teach the material to yourself, how is your experience improved by being in the class?

There are a couple advantages. One of the most obvious is the lower latency of responses when you have confusion or misunderstanding. In a lecture, you can ask a question and get an answer almost immediately. This is most useful (imo) with algorithms and mathematical concepts, because you can ask, and lecturers are often quick to provide insight, into the interrelationships between algorithms (both in Machine learning and in a more theoretical sense like computability). There are topics that come up a lot, and being able to have instant feedback on those connections allows you to spend less time misunderstanding than not.

That alone is a fairly weak justification, I think the stronger one is feedback in general. Watching lectures only gets you so far. With implementation of algorithms, often your feedback is testable correctness (although my experience in DS&A suggests that most people are capable of constructing incredibly incorrect models for things that perform well on some input, and even on decent autograders), but with things like machine learning algs and intuition about those algorithms, you can't get that. So the feedback that yes, your understanding is correct (even if that feedback is slow) is invaluable. In that regard I think online courses and MOOCs can be good, but MOOCs that don't provide feedback aren't as valuable. I've attended a lot of lectures, and I've ignored a lot of lectures. Listening to someone say something does not mean one has learned it.

I'd also note that, if I recall, the way that Isbell approaches teaching the material, vs. the way the textbook does are very different. Textbooks are (often) references. They provide information on what something is and how it works theoretically, but very often lecturers are able to provide the kinds of things that aren't (and shouldn't?) be in textbooks.

If I'm reading a textbook, its very likely that I want to know how to implement an algorithm, so I care that the algorithm for simulated annealing says that you jump with probability e^(D/T) > Rand[0,1]. Whereas in a lecture, I'm likely much more interested in the idea that simulated annealing is conceptually very similar to throwing a ping-pong ball into a large complex, convex plastic surface and seeing where it lands.


My criticism is precisely that feedback was lacking. The assignments were only graded on submission - there was no feedback there (likely because every student worked with different data so going in-depth would have required the grad student TAs to spend too much time per student digging in).

I don't agree that feedback during lecture is valuable or low-latency as you say - not with 100 students attending. It might work to ask a clarifying question here and there, but again - you're only in a position to take advantage of that if you're already comfortable with the material and are generally keeping up.

Books are different than lectures, sure, but I don't think there's much difference between attending a lecture with 100 students, or watching one online. Indeed many people claim the online way is better, since you can rewind and skip around, pause and lookup references, etc...


When I took it we were encouraged to use Weka for the algorithm implementations themselves. This certainly allowed me (and I'd never so much as touched machine learning prior to taking the class -- I took it on a bit of a lark that wasn't related to my research at all) to focus on understanding the behavior of the algorithms rather than worrying about hacking them together.

I'd agree that Tech has too few TAs for too many students, generally, for its graduate courses, but I don't know that other schools do a better job. A brief survey of the folks around my desk elicited howls of laughter at the notion of useful or accessible TAs in grad school.

> I agree that Isbell is a joy to listen to - he is charismatic, entertaining, and I too enjoyed his anecdotes. However, I felt like you would only get something out of his lectures if you already knew what you were talking about.

I think this assertion is, at best, too strong. A better assertion might be that his lectures depended on coming in with sufficient background.

As I said, I came into the course with no experience with machine learning at all. On the other hand, I did have a fairly strong theoretical computer science, stats, and linear algebra background. I will admit that may have made me blind to things he was simply assuming with respect to educational background that were not actually safe to assume. That said, I still refer back to his primer on information theory (http://www.cc.gatech.edu/~isbell/tutorials/InfoTheory.fm.pdf) when discussing work relying on it, so he certainly made some effort to fill in gaps as he discovered they were common.

> When I think about the quality of the class, I think about how responsive the class is to the individual needs and progress of the student.

For a graduate level course I feel a class clears this bar when it accurately and thoroughly documents the prerequisites. Now, I'm not saying Charles's class necessarily does this. As I said, I came in with a pretty strong background in what turned out to be more than sufficient, but with that background I personally felt his lectures were quite tractable, even assuming complete ignorance of ML itself.


These students spent most of their time finding implementations of the algorithms and hacking at them to actually run all the experiments. They then rushed through gluing the results together through some semblance of analysis. Alumni of the class I knew said the same thing about their experience.

Ironically, this sounds quite a lot like much of industry.


Or unsurprisingly...


yeah, true.


I also graduated with a MSCS from GT. While I agree that a Masters degree is not a good signal for a job candidate, having Georgia Tech as your last institution of study instead of your potentially "lower" undergraduate program is.

The question remains is if an online degree has the same credibility. Looking back at my time at GT, I cannot see how operating solo, without the constant feedback from your peers and faculty, is as good. There is more than just what is in the study material. The other question is if the entrance requirements are still as stringent.


Silicon Valley hiring manager here.

From my perspective, unfortunately, Georgia Tech has really diluted the value of their masters in cs degree. They have become a sort of immigration visa-mill with very many India undergrad -> Georgia Tech Masters of very questionable skill level.

Just my experience.


GT grad here (1999-2003). While I'm not Indian I do have a ton of Indian friends and yes GT does have a large Indian percentage (by observation from when I was there).

I can't speak if the CS degree has been diluted but I will say there is an enormous amount of extremely undeserved selective bias against Indian people for technology jobs. When US citizens even see Indian names there are less likely to hire (known as name bias).

Again I can't speak for the programs but my Indian friends that went to tech were at the top of their class both in MS and BS. Highly qualified. Extremely humble, ambitious and hungry.

Just my experience (and I run a recruiting software company so I see it at scale).

I compare this to the apathetic divas that I have met from Stanford and MIT (I live in Mass so I have met many MIT grads). I would hire a GT grad over them any day.


Indians have a stigma for a very good reason: the 5% top engineers are drowned out by the 95% posers used by body shops (Infy, TCS, etc.) that have literally taken over numerous industries in the US tech market.

I worked in India for one of these BPO companies and know what I'm talking about. If the good engineers from India want to reclaim their status, they need to push back against the flood of H1Bs from these companies.

But instead, the majority of HN (or at least the guys who do more hiring, less coding) keeps pushing for more and more visas when we should be urging Congress to reform the system to allow the talent to come in (with Green Card), while disallowing US companies from using it to lower wages for all US engineers.


I have no doubt about the stigma... but one should be careful about letting stereotypes into their decision process particularly when it comes to hiring and race. It is not just morally wrong it is against the law (at least in the US).

I'm sure the hiring manager who posted earlier will say it doesn't affect the decision but the subconscious bias is a real thing.


I concur, but I'd rephrase it like so: It's not just against the law, it is morally wrong.


CMU has done this too unfortunately with their online MS degrees.


Those degrees are not CS. AFAIK, CMU only has a software engineering online degree.


Sure, but... We have clients hiring individuals looking only at cmu and see an online ms tangentially related to analytics then they associate that with cmus world class ml program and then touting them in our faces as the latest and greatest in machine learning. When we interview folks from the same program they don't make it past our first round because they don't know technique or programming


>When US citizens even see Indian names there are less likely to hire (known as name bias).

You're doubly fucked if you have an Indian name and you were born here. White hiring managers automatically assume you're incompetent, and Indian H1B hiring managers are threatened because they fear for their job.

When I was younger, I found it odd that many of family members of mine would Americanize their name. Now, I've experienced the reality of it.


Damn. I'm a second gen Indian and this makes total sense. I may do an experiment and go with a western name just to see what happens. But then I'm reminded of all the other Asians who do that and think isn't it a little odd for an Asian to be named Winston Chang and more normal for something like wu Xi or something. Or maybe that's too nomenclature-normative and we should be more agnostic to the orientation of someone's chosen name


I get this too. However, I can say that it's not just Indians. There are quite a few people from all backgrounds who have questionable skill levels from prestigious schools and/or who have masters degrees. I've given enough interviews to realize that there is an alarming amount of people who can't figure out how to write an "addition" function given two strings representing positive integers in a 45 minute window. So, I honestly skip over the school and education in the candidate's resume and see what their work experience is (or side projects if they have that).


Yes it's not just masters and it's not just indians. I think everyone who has been in tech long enough can give many examples of people with great backgrounds who just weren't great engineers. Education is a signal for sure though I think - it shows a certain willingness to dedicate oneself, and a certain level of intelligence and aptitude to attain, and getting a M.S. or PhD or even a B.S. from a hard school is going to filter out a lot of people already.

I also think a graduate degree is necessary for certain types of work. For just bog standard programming jobs where you can read a web page to learn the language/framework/library, sure you don't need it. But for other types of roles (quant roles, more research oriented, ML, anything tech cutting edge that requires theoretical understanding), an M.S. or Ph.D. is going to be a gatekeeper whether you want it to or not.


Question for you if you don't mind...

I've been out of undergrad and working in industry for close to a decade as a Software Engineer and/or Embedded Systems Engineer. I feel I'm doing pretty well in my career, but I've been looking at the online masters in CS as a way of showing that I'm dedicated to continuing learning, and to maybe open up some new doors for myself down the road.

From your perspective as a hiring manager, would this be worth the time and effort? It's not like I wouldn't be interested and learning new stuff anyways, but if I'm going to go invest the time and money to do the degree vs. learning on my own, it would be nice to know if it was worth anything.

(No sweat if you don't feel like answering, or want to take this private. Thanks!)


I believe that a dedication to continuing learning as massively important in our field, so it is something that I always ask every candidate during an interview. Not everyone has time for open-source projects, blogging, what not, but anything is important. Following Martin Fowler in Twitter, receiving a newsletter, something, anything. Candidates that demonstrate no interest in furthering themselves is risky, but from themselves and the company.

That said, a masters degree is not necessary, it is an overkill. I rather see open-source projects.


I wholly agree with your first paragraph, and I'd elaborate a little on the second.

I see only an upside in earning a MSCS, however you do it. But while learning more principle and technique is always good, it's not strictly necessary and it's definitely not sufficient to outcompete other candidates.

Experience in relevant side-projects is a good thing. It shows initiative and passion and that you're more than just a serious student. Open source dev experience demonstrates your desire to create -- not just to design, but to actually make -- as well as your ability to work with others, especially distant others. Most pro tech work now requires not just up-to-date tools and techniques but also good communication skills, increasingly with folks who work away from you. Demonstration of such skills is unusual and desirable, especially in those just out of school.


Instead of editing what I wrote, I will comment on it.

In hindsight, looking back at my MSCS, I think the strongest point of a Masters is not the elevated agree, but the opportunity to focus on a specific field. If you have an interest in AI, go to GT and work underneath a professor with lots of experience. Do not get a Masters just for the sake of getting a Masters.

GT has tons of research dollars. I was paid the entire way there, even as a non-PhD student. At first a teaching assistant, and then a research assistant. You cannot get that kind of experience from an online school.


> That said, a masters degree is not necessary, it is an overkill. I rather see open-source projects.

There are companies where side projects or off-hours work on open source projects is complicated. Employment contracts that say the employer owns all of your work, on the clock or off, aren't uncommon. It might be easier for some people to get a masters degree, especially when employers are willing to pay for it.


For getting a new job, only do an online masters if you want to switch specialties (i.e. move from embedded to security or web programming, etc)

If staying in embedded will just focus on work experience.


I'm sorry you didn't like the on-campus experience at Georgia Tech -- but the online program sounds like a clear win. For less than $10,000 tuition, you could've gotten a top-10 degree and your $20,000-per-year salary increase... all while still working, so you would've also accumulated raises and experience while finishing the degree.


The question would be whether the time spent on this program compares to what one would be able to accomplish on their own, and whether the difference is worth the price tag.

From my experiences with GT, I am apprehensive about the quality of content - I assume it's coming from the same departments and professors that I had experience with.

From other comments here it seems that the approach this program took was quite different from the one employed on campus, so that apprehension may be unfounded - that is, the online offerings may be of higher quality than what students on campus receive. Still, I felt like I needed to post something to warn people that the branding of GT does not in-and-of-itself mean that the content will be of high quality. Students considering the program should try and find some way to evaluate this - are there sample classes or lectures posted online? Perhaps ask someone you trust in the industry to take a look and give you their feedback.

Still, I think students who are self-motivated should consider what they would be able to accomplish if they took some time to organize a study program for themselves. There are many free high-quality resources out there that could be used for effective self-directed study.

Students who are less confident about doing it on their own should be asking themselves what sort of support they expect to be getting from the program. Certainly there are many advantages in having things curated for you, as well as having access to discussion boards with other students going through the same material. Aside from that, many students (unfortunately, I think), need the external schedule and commitment - and for them, merely having an exam deadline, or the $10K investment looming in the background may be the thing needed to get through the material. Those students, too, should be realistic about the investment they are making and what they hope to get out of it.


Does it remain a top-10 degree if thousands of people take the course every year? Genuine question. I work in education, and we struggle with this selectivity vs. access question ourselves.


I agree, and the $10k tuition would be likely covered by your employer. Some of the more expensive online MS programs still have significant out of pocket expenses if they are $40k or so


[disclosure: GT CS alum]

>Andrew Ng's Coursera class on Machine Learning was the pedagogical highlight of my time at GT, and I did it on my own initiative (and it's free).

This is something I wanted to highlight from your post. I don't think this is surprising, nor do I think it is reasonable to state that a course (or a degree program) is poor quality because it didn't meet the standards of Ng's ML course. That is an exceedingly high bar.

Its something I noticed, because I am a recent grad, so while I was in my mid-level courses, and had recently taken Tech's intro CS course, I was able to watch (Harvard's) CS50 and other courses. But on the other hand, I've seen some very bad online courses. The successful and large online courses are successful and large specifically because they are head and shoulders better than the rest. And there are a lot of decent online courses, so to measure against what are some of the absolute best online courses is to measure against courses that have more resources, more planning, and more feedback than most.

(as an aside, they also have more incentive to be good, but that's a bit tangential to the point that they also have more opportunity to be good).

You type in "Machine Learning" on coursera and you get over 1000 results (not all of which are relevant, but assuming even 10% are), its little wonder that one or two are going to be better than the even the best courses that you'll take during a bachelors or masters, because Coursera offers more Machine Learning courses than most people will take in their Bachelors or Masters.

Combine that with these courses coming prefiltered (you've heard of the Stanford Course, but what about "Applied Text Mining in Python" from UMichigan, which for all I know might be great, but it doesn't come with the hundreds of recommendations that the Ng course does, so I don't know that it will be great) and you have a really great recipe for a bias against the in person courses.


This is interesting. I had heard good things about the program, so I'd love to hear more about what ultimately went wrong.

What track were you on? Do you think that had anything to do with it? What did your peers think about the program?

A $95 to $115k bump sounds pretty darn good. Did you already have a CS undergrad degree? Where from? Sorry for all the questions, feel free to share as little or as much as you're willing.


I was on the Machine Learning track. Already had a CS degree from a prestigious school. I took classes primarily in the ML concentration, although I had to take some courses in theoretical cs and they were similar.

I'd say my peers generally shared my opinion (classes not being very good). Many of them were trying to get into PhD programs so they were focusing on finding research opportunities and didn't care about the quality of classes much. Some struggled but blamed themselves for this rather than the class. (I'd say this was very common amongst the undergrads too).

Of the PhD students I knew, most were discouraged from taking classes altogether, since it took away time from research. This was true even in the first year of their program. The general attitude from that side was that classes were a waste of time.

Many higher-level classes were run as mini-research projects. You'd get some content, then the rest of the class would be forming teams, proposing project ideas, implementing, writing up results and having 'mini conferences'. I think faculty liked this since it was a good way to try out research ideas, recruit potential PhD students, and give their current students extra time to work on their research.

Nothing wrong with that format, of course, but the actual coverage of content was typically superficial. If you weren't already familiar with the area, you had to figure it out on your own as you went along. Also, this is not a class format that translates to online very well.


>Already had a CS degree from a prestigious school.

I do not. I'm self-taught and considering the online MS for the purpose of signaling that my skills are legitimate (and filling in some theoretical gaps). As a hiring manager, would this change the value of an MS in your eyes? Or still unimportant compared to projects?


As someone who had a BS in biology before earning a part-time MS in CS (in 1990) I can say unequivocally -- the degree was a life transforming game changer.

With a non-tech BS degree, all too few HR departments (esp in bigger companies) will invite you interview for a software job. Without the CS degree, I was a pariah with very limited prospects. Frankly I doubt that POV has changed appreciably, even after 27 years. Business-men/women are a conservative lot. They take as little risk as possible. If you lack credentials, they hire you, and you fail... they look bad and have a hard time explaining why they hired you. But if you had a relevant tech degree, their ass has far better cover.

Of course, if you already have a BS in CS, I can't speak to the value of adding a MS. Even when I earned mine, the incremental added value beyond the BS wasn't overwhelming. But some employers care more for advanced degrees than others. Uncle Sam and most large companies automatically kick you into a higher salary bracket if you have one.

It also doesn't hurt if the school granting your MS is renowned. Aside from silicon valley (apparently), I suspect 95% of employers will be very positively impressed by a degree from GT. I know several employers responded favorably over the years to the mere fact I had a degree from Johns Hopkins. Like it or not, your alma mater often matters.


Great point. MS degrees may have changed somewhat since 1990, though.

One problem is that MS degrees don't really cover the general curriculum. They're often, even when rigorous, used to allow students to focus on a topic or project that isn't as lengthy as a PhD. For instance, someone with a CS might be interested in numerical computing, and work on ways to solve various differential equations.

The downside here is that this means a math or physics major might get an MS in CS, and do some programming in numerical computing, but not know much about algorithms or data structures.

I'm presenting this in the context of a genuine, rigorous MS degree, because it doesn't need to be a watered-down experience to still show the pitfalls.

Some MS degrees do require certain core courses before you can apply - so they'll take a math major, but they'll require that this student complete certain undergraduate courses - some before applying, some while enrolled. This can add time to the MS degree but avoids that scenario I described above.

Of course, once you've actually taken those courses (say, a math major passes courses in data structures, algorithms, compilers, and operating systems), then the MS may not be critical for finding a job anymore. But the degree can help.

Unfortunately, I've noticed a trend toward discounting MS degrees or even holding them as a negative indicator. This is probably because people get an interview because they have an MS, but then are tested during a technical interview on general CS that they may not have taken.

Not sure of the solution. I think the best approach is to take promising students from other fields, but then make sure they've taken the additional core coursework. This would add some time to the degree, but if all MS students did this, I think the degree would be more respected.

As it stands, the BS in CS is respected, because it (if the school is accredited) must contain all those core courses that tech companies love to quiz people on.

Whether those topics are actually relevant to the job is an entirely different topic!


I'm an engineer that does hiring as part of my duties. I don't ever look at the degree.

To signal your skills, I'd think about the industry you want to work in, and try and work on a project that is similar to work you'd like to do.

For example, if you're wanting to get into Data Science, find a data set, pick a question and answer it. Build visualisations, implement ML algorithms, etc. Put your code up online and write a blog post (or several) about the process.

A year spent doing that would be worth more in my eyes than a MS.


Or start doing Kaggle competitions, which signals some objective performance too.


Depends a lot on the company. You will have more leverage with HR to negotiate salary with an M.S. for certain positions and companies.

I'd recommend it if you have the time. As much as HN likes to push "just show your github contribution", degrees do matter to companies.


That bump was written ambiguously / confusingly. I think parent comment met a $20k bump from $95k to $115k, not BS base + $95k–115k.


Ah, of course, you're right. That makes a lot more sense. I'm not sure what I was thinking :P


ah. First thing I did was search the page for "95" to figure out WTF was going on. thanks.


At least one prof there takes UML seriously, and demands that his online students use it. I count that as a bad thing, but what do I know?


What you say is often true, however there are a number of places that will shitcan your resume if it doesn't have an advanced degree on it. For example SpaceX, but there are others, often in technical fields.

Also, hang in there. The degree may not have helped your current job as much as you'd like, but it may help more at a future company. Sadly we often need to change jobs to get a real salary bump.


The great thing about the premature resume shit-canning is that it leaves a ton of talent available for smaller or lesser known employers.


I think you're looking at it in both a false comparison (opportunity costs for online are very different than your on campus experience; not to mention the explicit costs) and backwards (as to who is looking to get this degree).

The margins on adding a MS CS (or analytics) is less for a CS grad, but at 10k a degree and the flexibility of taking online they are huge for non-CS majors looking to pivot. 10k to bump your salary up 20k (while working and getting experience + raises) plus the knowledge add pays for itself.

Im biased on account of being in the program (supplementing my Electrical Engineering degree due to a change in career and life paths), and I know a lot more about graph theory, formal algorithms, and high efficiency computing than I did a year ago. These are things that help improve both your portfolio of rigorous projects (Im currently working to port over all of my high performance computing assignments to Rust) and assortment of tools for the ever annoying CS interview.


I was in the aerospace department as an undergraduate, and my impression was that everything at GT takes a back seat to the PhD programs.


This is pretty common at all the top Engineering departments, nowadays.

My doctorate was at Texas, and it certainly catered primarily to what brings in the $$: e.g. research.


Yep, welcome to every research based university in the world. Even B.S. degrees take a back seat. I think OMSCS is good because they seem to at least be trying to improve the non-research track experience.


I'm enrolled in the OMSCS program currently (nearly graduated) while working full time. I started the program because I was already taking the online courses with Coursera, edX, etc, and it felt like a natural fit to get a degree while I continued to do so.

I didn't have a Computer Science undergrad degree, so perhaps I have a different outlook on this than you did. I'm currently working as a software engineer, so I'm also not forgoing earning a living by taking the time off from school.

In other words, while I can understand why you feel disappointed by your educational experience, there are other lenses through which this program makes sense. I feel good about having gone through it so far and I'm looking forward to finishing.


It sounds like you did the on-campus program at GT, so you took time off work to complete it. It's hard to argue with the fact that losing the wages to do that is a lot of missed opportunity.

However.... I think majority of people that take OMSCS (I am in my 2nd semester) and this new OMSA program do so part time while still maintaining their fulltime jobs and families.

Also, why the throwaway?


It strikes me as odd that the parent used a throwaway as well. What are they trying to hide?


Is not another possibility that they'd like to keep face / maintain positive relationships with their network from the school?


Maybe they don't want their salary being public?


I'm enjoying the MSCS program online so far and am also doing the ML specialization. I work full-time as a software engineer and just do the coursework part-time. My experience so far is that the assignments and learning are as rigorous as you want them to be.

I'm getting exactly what I'm looking for out of it (a somewhat structured environment to learn in), so for me I would say this isn't a losing proposition.


I am a current OMSCS student.

Your situation is anecdotal at best. You are critiquing an in person experience to an online experience.


> You are critiquing an in person experience to an online experience.

GT goes out of its way to say that the online experience and physical experience offer the same degree, is it not fair to compare them?


Same degree != same experience. Just like the same course within the same institution can offer different experience depending on the instructor.


Isn't that the norm as you continue along the education path?

E.g. someone who did a PhD with one advisor vs another


Perhaps this is the rare place where a more impersonal interaction helps avoid some of the negatives outlined above.

Anecdotally I've felt all of the professors are eminently interested in interacting with MS students online.


Really? Pretty much all feedback for OMSCS has been very positive. It sounds like you're bitter about something, or had a particularly bad experience. Can you provide more details about classes you thought were poor and what was poor about them?


I am bitter about having spent time, money and emotional energy on something that I felt I got no value out of, and I want to warn people thinking about doing the same.


Fair enough. I think your complaints though can apply to most degrees attained at big research universities. Certainly my own at a top undergrad C.S. had its share of terrible teachers and classes - it's a problem across the board, not just at gatech. And by all accounts, as OMSCS is focused on the classes and not research, much of this has improved (with some outliers like the CS6505 algo class, and some others).

My own experience was doing about half of an M.S. about a decade ago before dropping out to go right into work, due to money constraints. I don't regret taking those classes at all though - I learned a lot because I put a lot into it, and it's knowledge I've used throughout my career. I find it hard to believe doing an M.S. at gatech would have no value at all - I guess it depends what you plan on doing and how you will use it.


> From my point of view, this program is a losing proposition for any potential student.

Although I agree with your sentiment (formal education has a lot of flaws), a full-fledged degree potentially solves other problems than just improving your resume to get a better/higher paying job for engineers.

Family pressure, lack of confidence that comes with not having a formal CS undergraduate degree, or motivation and structure that comes from paying for a formal program could all contribute to someone choosing this path. A $10k, online masters program from GT seems like a good option for some people.


According to http://www.mastersindatascience.org/schools/23-great-schools... it's one of the best data science programs out there. Is there any other one that you can recommend?


I haven't gone through other programs, so I can't say from personal experience.

There are no programs that have stood out to me during hiring to predict the quality of the candidate.

If you're a student looking at programs, I would prioritize the amount and quality of individual attention you stand to receive. A self-directed student can do well anywhere (including on their own). If you're not so stubborn/resilient, having a good community and mentorship to help you overcome difficult times is key.


Perhaps The degree matters to people who are transitioning in from a 0 experience background?


I completed an Information Security and Assurance MS at a different school and in retrospect, I wish I had done it online instead.

I could have done it for 1/3-1/4 of the cost and in the same amount of time but with far less time spent commuting.


For what it's worth, GA Tech is an amazing school, but I do think they are far more known for their traditional graduate engineering programs (aero, mechanical, electrical, etc.) than CS.


These are sadly not linked to the sources, but they have ranked high for a number of years in CS - http://www.cc.gatech.edu/facts-rankings.


It is kind of funny in a post about a program which costs under $10k to have the top rated comment complain about a similar one _only_ adding $20k/yr of value.


> in my experience the degree ended up being worth a $95K to $115K bump in starting salary.

Wait... isn't this kind of a good reason to suffer through the course?


also just read, think, build, repeat, for free. at own pace. own schedule.


I have both a B.S. and M.S. in Computer Science. I didn't get my Masters because I wanted a higher pay grade (although the company I was working for at the time did reimburse a large amount of it), it was to get out of industry.

From my first job, I realized life in a cube wasn't for me. I really wanted to be in front of a classroom. I realize there are problems with academia. I know you have the same squabbles and competition you have in the corporate world, and seeking certain grants to keep yourself afloat can cut into the research you actually want to do.

Still, I really wanted to teach. I've seen so many professors who only work one or two jobs, or go straight from BS -> MS -> PhD with very little industry experience. I wanted to be a different type of professor with plenty of real work experience to drawn on and teach from.

Grades don't matter. I've found that's very true for industry. Having a GPA on your CV doesn't really mean anything and most people leave it off. However, it has a huge impact on getting into degree programs.

I only had a 2.5 undergrad and even though I got a 3.2 in grad school, it wasn't enough for most programs I looked at. I attempted and failed to get into 8 schools back in 2009 (ironically, one that I later worked for and could get free classes at. PhD programs however, are full-time).

Today I have three publications that I'm 2nd author on, and in 2015 I attempted to get into school once again. I contacted several professors. Most simply don't write you back, but even when I got in touch with several schools, many simply didn't have any professors who were willing to take students in my field (environmental sensor research).

It's really competitive to get back into school and there is a massive disconnect right now between industry and academia.

You get out of any education what you put into it. You can leave with just a basic understanding of computer science and only know two languages leaving an outstanding program. You can also go to a crap program and push yourself to learn more on your own; using what professors teach as a jumping board for a lot more.

The TL;DR I'm getting at is that masters programs do have a purpose: getting you into a PhD program. If your work pays for it, it might be worthwhile for the additional title, but if not, you're not going to learn anything you couldn't apply yourself to on your own.


> The classes were of very poor quality - it was clear that they were a low priority for most faculty.

I took a master's in aerospace engineering at a top tier school and I wonder if this is the norm for grad engineering courses, and for many lower-level undergrad courses as well (think massive freshman calculus lectures). To calibrate what you consider "poor quality," how did you find the quality of your undergrad engineering courses?


This is great news. However, anyone who's used Piazza (the main "classroom" tool for OMSCS) knows that it's hardly ideal. I think a better collaboration/discussion tool is imperative to making the experience better for the "average" student.

Sure the top students in the program are going to do well, by definition, but there are plenty of more "middling" people like myself that can only be brought up to the next level with proper discussion/interaction with classmates. From my experience even PHPbb would be a more effective tool than Piazza.

---

Suggestions (if Piazza folks are reading):

1. Allow one to delete follow-ups.

2. Allow students to create private "study group"-like threads that aren't in the main feed.

3. Make it easier to upload pictures and other content.

4. Make things live. Normally this wouldn't be necessary, but anyone in the program knows many students post the same thing at the same time as a response to an event (like an email). By doing this you prevent redundant threads from being created.

5. Use some sort of up/down voting system that way the community can self-regulate.

There are plenty more things I'd improve, but for the sake of brevity those are some I just came up with on the spot.


edX (the partner through which Georgia Tech will be offering this program) uses its own homebuilt forums/discussions software, which offers many of the features you list. It's also open source, so if you or others have more discussion features in mind and have Python, Ruby or Backbone experience, PRs are welcome!

Disclaimer: software engineer at edX, have worked on discussions features in the past. Happy to answer questions.


I have taken over 30 courses on edX in the past few years (many more on Coursera). Some of those courses used Piazza, most the edX forums, so I know both systems. I also was a Community TA so I know the (few) options a CTA gets on edX.

Overall, IMHO Piazza clearly has far more features.

That said, I still prefer edX forums simply because I hardly ever need any of the Piazza features - and the Piazza GUI IMHO is much worse than edX especially for the target group. After edX implemented the sort-option "by activity" and "show only unread" my major complaints were solved.

--

By the way, since I hope you read this reply, the worst by far on edX is that the darn page just won't stand still!

Please stop the "convenience scrolling (by Javascript)". Also, the height of the page changes when I select a comment that does/doesn't fit in the viewport (long threads vs. no-responses-yet comments, for example, and that too triggers automatic scrolling.

Next, the size of the text box changes! I use Chrome to make it much larger to see my entire long and carefully crafted and formatted comment, then I switch to another tab to do more research for my reply, but when I click back into the textbox it shrinks back to its small default size. Could you please leave my manually-made-large textbox as it is?

No changes of scroll positions, no changes of sizes, no changes of anything, please. Not just in the forum, the course pages have the same annoying (anti-)"feature". I find it very inconvenient when the GUI changes under me, it's the GUI equivalent of walking on ice.

I would also enjoy a feature to "mark all as read", so that I can use "show only unread" at any point in time. Right now that feature forces me to have clicked on each and every comment before it is useful.

Life update would be "nice to have" too, especially for a TA (if it's too expensive for server-load, how about offering it just for the TA and STAFF user groups).

What is also missing is even the slightest hint (in the comment editor, or anywhere) that you support LaTeX style formulas! As well as some help for beginners how to use it.

I know Christmas was last month, but that's my wishlist :-)

What I don't miss are votes. That always gets misused, and it is of very limited benefit. I see the value of votes in forums on something like reddit, I don't see benefit in edX forums with a focus on Q&A. Especially not down-votes. Even the "pin to top" doesn't really work: At least 70% of users don't ever notice pinned posts. If there have to be votes, do it like Disqus: You can see who voted. Or instead of votes do what Github did in the issues comments.

By the way, why do you still have votes at all? They are only displayed if anyone specifically checks them in a given comment. They used to be shown in the comment overview on the left. Right now the "vote" feature can be removed and nobody would notice.

Some random ideas:

Feature: Allow Staff and TAs to post without their status. Just like on reddit. Not everything I had to say was "official", and one reason I turned down several invitations to be a CTA on edX was because I really hated to have a green banner around every single one of my posts. Too much pressure, and just because I'm TA doesn't make all my answers "precious".

Feature: Allow admins (TAs, Staff) to merge threads. For example, the introductions at the beginning where 500 people post their own "glad to be here" thread instead of using the pinned(!) "Post your introduction here" thread, or when there is an issue and 50 people each report it (even when the last 20 new threads are about that same subject, most people post immediately before looking at the forum).

Feature: Detect if you responded to this person in the past. It's nice and gives a feeling of familiarity to find out you talked to someone in the past.

Feature: Geolocation. Show where the other people (in the current thread) are located.

Feature: Combine Wiki and forum: From within the forum let people select comments and/or threads for the Wiki. Ask the for some additional information, like choosing a Wiki page/section. This can address the problem that good comments are quickly buried by all the new ones.

Bug report: It seems right now the "Section" or "Chapter" or whatever you call it is not displayed in comments.


Thanks for the feedback - we hear you and I myself have encountered a lot of the issues you mention. I've passed this along to our product team and I'll see if I can turn some of the easier stuff into tickets myself that we can groom next time we jump back into this code.


For almost every course I've taken in OMSCS, I always run into those issues. I'm pretty sure Piazza team knows about these problems too, because I had these issues since I was taking courses in undergrad (4-5 years ago). What this makes me think is that Piazza is just incapable of improving its own core product because it's struggling to monetize and generate revenue. I think Piazza in its current state just doesn't work at the scale of OMSCS. It could work with class size of maybe 30-40 students. I would gladly switch over to another product if it was offered as an option.


As a current OMSCS student I have to agree that Piazza is less than optimal. I've found that in order to be successful I have to put in significant effort to communicate across all channels - Piazza, Slack, Hangouts, HipChat, email, Skype. The classes do vary in difficulty and polish. I definitely have had some negative experiences with students that weren't prepared or weren't doing the necessary reading and studying.


We're using Slack the product design course I'm teaching at University of Michigan this semester[1]. Not only does it do that stuff better than Piazza, but it'll get students used to the tools startups use for communication (though I have my issues with Slack).

[1] http://umichdesign.com/


Your second point rubs me the wrong way, a little bit. You probably didn't mean it like this, but... I think educators should have the education in mind first, and employability second. In this case, nobody is going to put Slack on their resume, so... I just find the argument strange


I could definitely see why you read it that way! I just meant that Slack has some drawbacks, like any tool. Specifically at work, when large groups are collaborating on important projects, I've been relying on wikis, email, and issue trackers more.

If the same issues creep into the class, we'll reconsider Slack. What probably won't change is the popularity of online collaboration tools for all workers. Fostering a community of similar learners to ask questions, share work, and help each other is one of our goals for the semester.


As I heard it put when I went through GT, "We're training you for the last job you'll ever have."

The more I'm out in the working world and interacting with people from a diversity of educational backgrounds, the more I agree with that approach.

(I'm specifically thinking about the "No, we as a profession tried that in the 70s, and here's why we decided it was a bad idea" moments)


Nobody puts bash on their resume either but in my observation interns that come in with extensive command line/tooling experience from school (myself included) are much more likely to be seen favorably and converted to full time because they can spend less time fighting with their computer and more time delivering.


Bash is maybe not the best example because it's indeed a skill listed for many devops positions.


When I first started doing Udacity they used Piazza which was okay. I believe OMSCS is going through Udacity also. We eventually switched over to Discourse I believe and it addresses most of your concerns. The search and duplicate checking before posting is great.


Many of the students and TAs are also on the slack group, omscs-study. It's far from ideal because it's "non-official" but it addresses a lot of these complaints.


Piazza has been a pretty good tool IMO. I haven't used it in the context of the OMSCS, only in all my undergrad classes at Berkeley, but it's been a really helpful tool when there's good moderation from the Professors and TAs.

Maybe this condition does not hold true for the OMSCS, but I think almost all your problems can be solved by a good moderation team.


I agree with you about Piazza. I was always very active during the OMSCS program on Piazza, but it didn't seem ideal for those "middling" folks. The biggest problem was important discussions and ideas getting buried. There just wasn't a good way to keep track of it all.


I'm currently in the Master of Science in Analytics program at gatech, so if anyone has any questions feel free to ask.

My experience so far has been excellent. I just started my second semester, and I can say that the curriculum covers exactly what I wanted to learn with the exception of one class. The program is extremely practical, it's only one year and is focused on getting the students jobs. The professors are great, and I highly recommend it to anyone wanting to get into the field.


How much statistics is involved? I'm asking because I have a friend who is interested in math and statistics but wants to go to grad school for something a bit more practical, while still having some challenge in terms of statistics.


I'd say it's very statistics heavy, but it depends on the individual. They offer three different tracks: computational, business, and analytical tools. If you pick the analytical tools track your classes will be more stats heavy.

Most of the core classes (like machine learning) are more math based. In machine learning, it's done from a mathematical/theoretical approach. Another example is regression analysis, where you learn the math before doing the practical work in R.

I have a weak math/stats background but a strong software background, which also aligns with my interests so I'm doing the computational track. As I mentioned before, most of the core curriculum is math heavy so I'm learning that aspect, but I'm also getting a ton of practical experience in machine learning and big data work.


>"A third track, Business Analytics, will be eventually be added as an additional option." (https://pe.gatech.edu/online-masters-degrees/analytics/progr...)

Looks like the business track isn't offered in the online program (yet), which is weird because it looks like all the requirements are offered online.


I'm curious to learn more about the business track, do you know where I might be able to read more about what is covered? Thank you.



Awesome! Thanks for letting me know. Hopefully after completing the program you still enjoyed it :)


What classes have you taken so far and what did you learn - very interested in this program.


In my first semester I took:

- CS7450: Information Visualization. Basically learned how to create useful data visualizations. Loved this class

- CSE 6242: Data and Visual Analytics. This class is interesting because you learn a very wide breadth of tools. We learned visualization (D3), big data processing (hadoop), and analytic tools (random forests for example). This was my favorite class so far

- ISYE 6414: Regression Analysis. The theoretical math parts of this class were really hard for me, but learning how to do practical regression analysis in R was super valuable to me.

- ISYE 6644: Simulation. Loved the professor for this class (Dr. Goldsman) but the material didn't seem very useful to me. Knowing the general approach of simulation for modeling is useful, but we went pretty deep into the math that I don't think will be useful in the long run

- ISYE 8803: Intro to Analytics. This was the most practical class I took and was taught by the head of the program. You basically learn all of the analytical models for the first 2/3s of the class, then in the last third you look at case studies and how to apply them.

Hopefully there's enough detail in there for you, let me know if you have any other questions


Wow, Dr. Goldsman. Glad to hear he is still an amazing professor - was one of my favorites as well.

Thanks for all of these comments, great to have some inside knowledge on this program.


This is great thank you. I am applying for the OMSCS currently but this seems to be a better fit for me as I am looking for a combination of math and practical experience with modeling.


Can you share some of your syllabus content? I'm interested in the program and would like to know if the content is stuff I'm already familiar with.


I'm currently in my second semester in the Master of Science in Artificial Intelligence program at UGA, I'm curious did you consider at it as well?


I did not look at that program, if I remember right I applied to UC Berkeley, Northwestern, Columbia, GaTech, and VaTech


What the factors for an application to be granted, can anyone get in?


Not sure I can speak to this question since I'm not affiliated with admissions at all, but I can tell you the makeup of my cohort.

Most (I'm guessing 75%, possibly higher) have some work experience. Most have either strong math background or strong software background but there are exceptions. Lots of former engineers of all kinds, chemical, mechanical, software, etc.


Can anyone speak to the value of the general online CS Masters degree offered by Georgia Tech? I'd been considering it, as it allows you to keep working while you improve your resume. I'm curious if employers (1) can tell it was completed online and (2) distinguish between individuals getting the residential MA versus the online MA. Thanks in advance.


(1) No. (2) No.

"Will the degree I receive from the OMS CS program be the same as the on-campus MS in Computer Science or will my degree say “Online”? Your diploma will read "Master of Science in Computer Science," exactly the same as those of on-campus graduates. There will be no "online" designation for the degrees of OMS CS graduates."

https://www.omscs.gatech.edu/prospective-students/faq

---

An employer could simply notice that your location and your school are in different places. However, IMO it's more impressive to have been working a full time job and doing a degree than the opposite.


I did the MSCIS program through Boston University several years ago, and this has been my experience. Employer's will figure it out, but they actually tend to be more impressed once they find out I was working full time and going to school.


I live in Atlanta and work with a bunch of Tech grads. Tech is one of the most prestigious engineering universities in the southeast (if not the most), and its degrees are tremendously valuable.

AFAIK, this is Georgia Tech's second online masters degree course, which demonstrates that the university now stands behind their online degree program. One of my coworkers is currently enrolled in their other online masters program, and he speaks highly of it.

If this is anything like their first online masters program, there is no distinction between the online and on-campus diploma. The degree is a full-fledged Georgia Tech degree. This is what makes it so attractive--employers and other educational institutes won't know you didn't physically attend the campus.

I'd be happy to get more of my coworker's opinion on the program if you like. I'm interested in it myself...


While technically GA Tech makes no distinction between the two degrees, in practice employers can often tell. However this isn't always a bad thing.

I'm a current student and I switched jobs about halfway through the program. I'm living in Austin so it came up in the interviews that this was an online program. I explained to people that I was doing the online degree in my spare time but taking it slower and that all the courses were the same as the on campus counterparts. Generally speaking the interviewers seemed to be impressed by this and said that it showed a strong work ethic.

I can't give hard facts about the value of the program but given that it only costs between $7k and $10k to complete I think it will pay for itself very quickly and perhaps already has.


There is a good podcast/audio interview[1] with C Charles Isbell, Jr., Professor and Senior Associate Dean at GA Tech., on the TWiML podcast. He discusses how their first online master's program has worked, and I found it quite informative.

1. https://twimlai.com/twiml-talk-4-charles-isbell-interactive-...


1. No distinction 2. Not unless they ask you

And everyone who's been exposed to both says it's the same courses and rigor as the on-campus version.

(Source: 2 classes from finishing)


> And everyone who's been exposed to both says it's the same courses and rigor as the on-campus version.

I am curious: who in the world would do both?

A more serious question, since you're going through it now: is there a thesis component to the online MS, or is it just coursework? If there's a thesis (either required or as an option for more research-oriented students), how does the thesis mentoring at a distance work?


I've taken some of the courses that exist online on campus and they are the same. I used the videos for review.


> I am curious: who in the world would do both?

Nobody, they're TAs now. ;)


Ah, right, TAs!

Got any info for the lazy on the existence of a thesis track?


No thesis option.


Good to know. Thanks!


Thesis track isn't offered and I don't think there are any plans to offer it.


It's something I haven't looked into for many years but I find it interesting that Masters engineering programs seem to span the range from coursework-only one year programs to two year plus programs with a thesis. With relatively little correlation between that and the overall reputation of the school/degree.

In my experience, the thesis is a huge part of the degree when it's present so I find it at least somewhat curious that some (many?) programs that are generally considered quite good don't have one.


It'd be pretty unscalable for the (online) Georgia Tech program due to the way thesis research funding works.


Oh, I certainly understand that. I just find it interesting that there often doesn't seem to be a big distinction drawn between Masters degrees with a thesis component and those without--even though that's a pretty big difference. It's hardly unique to Georgia Tech. My understanding is that many Stanford Masters degrees don't require a thesis either.


It definitely is interesting. I did most of a Master's in CS at a state school ~2013 that offered both thesis and non-thesis options. The non-thesis was newer and more popular for part-time.

Another thing one professor explained to me is that the standards for a Master's thesis are actively changing. You can either do a glorified undergrad senior project (but with you doing all of the work that a small team might do in undergrad) or intense publication-worthy research. The latter was mostly people going forward with a PhD to follow. I definitely went in to the degree with the impression that all Master's students were doing a thesis in the second category, but I think this is a case of the times are changing.


I did a resident MS CSE around the time they started the online program. While for the classes that were also available online they seemed equivalent (usually just recorded versions of the same class), there is one big caveat: most of the courses I took during my MS, or at least most of the most valuable courses I took, were not offered online.

My BS CS was also from GT (several years before), so much of the core course list available online were slightly more rigorous retreads of distributed algorithms, simulation architectures, etc. already covered late in undergrad. The most valuable courses in my MS were special topics courses that, at least at the time, weren't available online, many of which were in other departments as part of the computation + application domain interdisciplinary approach of the program.

That said, the core courses that were also offered online were generally quite good, and a few were exceptionally great. Rich Vuduc's HPC applications course comes to mind.


My wife and I have done some of the same coursework (for different degrees), me on campus and hers online. I actually would have preferred online. Rigor seemed equivalent, but I find the ability to pause and rewind lectures invaluable.


Being almost done with the program, would you recommend it?


I finished in December. Definitely rigorous and challenging.


A colleague is nearly complete with his online CS Masters from GT. He has spoken well of it, so much so that another colleague has already applied and been accepted. I considered it as well, but I'm tired of traditional school and don't see a need for the MS when a BS is doing me fine. Maybe some day.

So based on what I've seen and read, I could recommend it.


They can certainly tell it's online if you completed it during a time when you were working somewhere other than Atlanta.


If there's any degree that's ideal to being completed online its CS


Having taken a number of MOOCs as well as having a traditional engineering masters (not CS), I'm inclined to agree.

- Although not universally true, you tend not to need labs stocked with equipment that aren't practical for an individual to purchase. (Though, yes, CS degrees can be oriented around hardware.)

- Automated grading of problem sets/tests seem to work better with software than just about any other topic of MOOCs I've seen. (Though that's probably not an issue for this sort of paid program as you can have paid TAs and professors directly involved.)

- Remote "teams" can clearly collaborate effectively on projects etc. as demonstrated by the fact that they do in many companies and on many open source projects. That said, a big part of a masters degree is going to be individual work anyway.

ADDED: As someone else mentioned, in-person mentoring would still be a concern of mine but that's probably a tractable issue.


1) Nope. Same degree and same diploma. 2) Only way to tell would be to infer from your location or ask you outright.


OMSCS students can also get GaTech student ID's for campus privileges (libraries, rec center etc.).


How would you apply for this as a student? Could you get the ID mailed to you overseas for example?


No, you have to go to the campus to get one.


I'm waiting for the online, low-cost undergraduate degree of comparable quality to the "real thing". Maybe it's already here. I recently checked up on tuition at my alma mater and almost barfed. With a kid on the way Mr. Market has 18 years to figure this out for me.


The University of London external program has been around since 1858, so hopefully it will still be around 18 years from now :)

http://www.londoninternational.ac.uk/

Three of my kids and I are are doing CS degrees from here right now, two of us while working full-time.


Or you have 18 years to move to another country.


For comparison: Master of Computer Science - Data Science (Univ: Illinois, Coursera).

https://www.coursera.org/university-programs/masters-in-comp...


UIUC has a great reputation especially for research. I haven't heard of their online MS yet, but their undergrad program is very well respected.


I am skeptical that this program will be a good signal for hiring analysts. In my experience, there are two things you need to select for:

(1) Understanding statistics. Hopefully this program will take care of this requirement, but it's not hard to find these people anyway. There is an infinite supply of science PhDs fleeing the academic job market.

(2) Behavioural/personality. People who will do well at the actual job. Example: can you tell when a PM is asking you to answer the wrong question, and how do you handle it?

You can easily find (1) with screening questions, (2) is the hard part.

But, I guess if you think you have (2) as a future analyst, this program could be a good way of getting (1).


Is there anything similar to the Online Masters but a Bachelor's degree? Most of the online universities like WGU seem like a get a bunch of certificates then you graduate.


I went to WGU and graduated with a Business Management degree. I did my homework before I went and the degree is fully accredited, with some students moving on to graduate programs. I only got one certificate during the entire experience and that was through CompTIA when one of their tests counted as the final exam.


What do you mean exactly? WGU is accredited to grant Bachelor's degrees (and certificates).

http://www.wgu.edu/online_it_degrees/data_management_analyti...


FSU and Arizona State both have online "ordinary" CS bachelor's.


I thought ASU was software engineering, and not CS. However, they are very similar.



Oregon State has a reputable online CS post-bach degree for those who've already finished undergrad but want to go back.


Sorry for getting off-topic but:

Is there any business in creating a better "classroom" experience that what ex. Piazza is doing?

It seems like an are which could be improved immensely design/ux wise but it also seems like it could be an area where that's not really going to make you successful because the distribution is already owned by someone else.


One place where Piazza really excels is in their Sales. They used their network to get the big schools, now getting the smaller schools is relatively easy. I can't imagine a startup/small business selling software to say for ex. Harvard, without knowing a few professors inside Harvard. You can definitely make a app that students use, but getting professors on the platform and getting the selling part right would be incredibly challenging.


Someone else mentioned here that the reason the software is poor is that there is not enough money to make it better. Not sure if that is true though.


I'm currently enrolled in the OMSCS program, and so far I would call it so-so.

I joined the program because I come from a non-CS background - undergrad in math, work in an unrelated field: consulting. I'm trying to pivot into a ML Engineer career. If you want to learn ML, you're better off going through the Ng Coursera course and from there pursuing some personal projects. The primary value of the program is the ability to get past recruiting coordinators simply due to the fact I'm enrolled in CS program.

The two undergrad CS courses I took at Berkeley were more rigorous, and were superior from a skills development perspective. But at the price, the OMSCS program is definitely worth it for someone coming from a different background.


Anyone have experience with this program without an academic CS background?

As someone with a BS in Materials Science & Engineering (at best a tangentially related field via sparse EE coursework) who does some level of programming at a tech job now, I'm curious what my prospects for admission would be. I'm confident I could handle the coursework, provided I could get my foot in the door.

As a related question, they mention taking courses to fill holes - are they receptive to Coursera offerings?


Yes, many of our students come in with either tangentially-related backgrounds or even unrelated backgrounds -- we look for students with outstanding analytics potential, regardless of background.

And yes, online learning and/or self-taught learning is definitely fine as hole-fillers; we just want you to have the necessary background to succeed, and however you get that background is up to you.


Appreciate the feedback!


I feel $10,000 for an online course is way too much. Just because it carries a label of university doesn't make it worth it. Almost all of the knowledge is available online for free. Although a university course gives a structure around a subject and provides learning resources & materials but universities have to realize that because of this many people will not take these MOOCs. Because education is a business, future generations will turn out to be illiterate.


>I feel $10,000 for an online course

It's not just a course it's a degree. When you graduate you have a Masters degree that is identical on paper to an on campus degree.


It's $10K for the entire degree program -- 10 courses. That's $1k/course, almost certainly the cheapest college degree in America.


...have you looked at the price of comparable online CS programs? They're often much, much more than that.


I'd definitely be wary of devoting 1+ year of my life full-time to "save" money on a program that costs "justs" $10K/year -- without looking at alternatives that might cost a bit more, but provide a much richer experience. (Yes, I have great deal of categorical skepticism about full-scale online degrees -- as opposed to occasional online courses -- in general).

Because even if you're unemployed, your most valuable resource is your time.


> Because even if you're unemployed, your most valuable resource is your time.

*Assuming there's enough in your savings account to cover expenses


Believe me -- I've been there, and I get where you're coming from with that.


Anyone have experience with FT online college courses? Would it be possible to both work FT and complete the courses? Or would it best to work PT for a year?


I am in my final year of a BSc in Mathematics with the Open University in the UK. I have been working full time throughout. The first couple of years it was fairly easy to stay on top of it but as the complexity increased it has definitely been a hard balancing act.

However, if you have the motivation then it's certainly do-able. My work was fairly intense too so as long as you are comfortable with giving up your weekends and have supportive friends/partners then it works just fine in my opinion. You get used to studying as your "fun time" - eg when I commute I spend it reading course notes, I play next to no PS4 games these days and I watch very little TV. I did think about taking a work break to totally focus on the course but in the end I've not needed to and find I prefer the brain ping-pong.

As someone who was in a relationship for 5½ years and is now single if you have a partner do talk it through with them. Be as supportive as you can of them on your journey. I'm pretty sure one of the reasons I lost her was the intensity of the last year or two. That was definitely exasperated by the workload and my general need to dedicate my weekends to exams/coursework/studying.


I got my bachelors while working FT. I did well, and it was manageable. My only caveat is examine your other obligations outside of work and school: family, hobbies, etc. Your time will be severely limited.

It's like running a side project that's actually used and not just for learning/experimentation.


I finished the OMSCS program while working full time. I think most can do it unless you regularly work significant overtime or otherwise have a significant lack of free time. Those with families, kids, etc. seem to do best taking one class per semester. Those with fewer such responsibilities can take two per semester.

Also: Even at two classes per semester it takes two years. One class per semester, a bit over three years. It does take some determination to see it through to the end.


I'm currently seven classes into the OMSCS program (one class per semester since 2014), work full time, volunteer as a FIRST robotics mentor, and have three kids and a loving wife. I have no free time and life is good. However, if my wife wasn't onboard and encouraging me to go through the OMSCS program, I wouldn't be able to do so.


As a current OMSCS student, it largely depends on your CS background, work hours, and which course/program. So far, it's been working pretty well for me as OMSCS has a lot of info about each course (check omscentral.com for course reviews), and I've been scheduling my future semesters based on course workload.


I'm not yet convinced that online learning is an equivalent replacement for a university degree. Exceptions do exist. For the most part, people graduate from these online universities without the skills needed for the jobs they want.


From my experience people graduate from traditional universities without the skills needed for the jobs they want. For example, how on earth can you graduate with a degree in computer science but never used version control? But I've seen it from our new hires. Version control should be taught the first day of CS101, that's where I was first exposed to it.


Because that's not the point of academic degrees? They're not job training certifications - you don't need a B.S. to program. Programming and engineering skills are auxiliary to computer science.


No matter if it's the point of them or not I was responding to "for the most part, people graduate from these online universities without the skills needed for the jobs they want." Pointing out that it's not unique to online universities.

(Either way, if you are going to teach programming at all version control is a big part of programming so it should be taught.)


That's a strawman argument so I'll put it this way: I have never interviewed someone with an online degree and walked out of that interview with a positive experience. Online education needs to improve if it's going to be on par with traditional degrees.


Huhh? How's it a strawman? Strawman: an intentionally misrepresented proposition that is set up because it is easier to defeat than an opponent's real argument.

I am not misrepresenting you, I m not really even arguing with you or disagreeing with you all that much.

I agree, online degrees are not providing job skills. But neither are many (not all) traditional degrees. Just one example is people fresh out of school who have never used or even heard of version control. Then there's the "can't do fizzbuzz" example.

This isn't even exclusive to CS degrees.

The reason I choose my degree program is it advertised itself as career focused education.

Either we should make education more career focused or accept that universities aren't primarily for job training and find alternatives.


Probably should learn it before that if you'd like to be a programmer.


Are both CS and Analytics degrees (from Georgia Tech) available to people outside U.S?


Yes, but you need to pass admission process (likely somewhat comparable education to US)


Anyone know if the GRE is still required for someone who's been enrolled in a traditional Master's in CS program before but with a GRE exemption?


GA Tech's CS program did not require the GRE, partly for the reason you state. There is still the usual admissions process with old GPAs and reference letters. Instead of GRE scores and very tough standards, students are conditionally accepted until passing 2 foundational courses within the first year. Hopefully the new program does the same, but it doesn't look like they've officially stated that yet.


Their FAQ states that the GRE is not required at all.


The fact that the Masters in CS and presumably this degree both require having a traditional bachelor degree as a prerequisite seriously limits their usefulness and their reach.

Are there any similar tracks that do not have this requirement?


the price and convenience are hard to ignore, yes there are some unideal aspects of the program (like the software and collaboration/discussion tech) but all-in-all what a great opportunity.


I'm not entirely sure how this is such big news. It costs the same as doing it on-campus here, including all hardware and books etc. you might need over a ~4-5 year span.


Is taking the GRE a requirement for admissions? The program looks very interesting but I can't bear to take the GRE after nearly 20 years of work ex.


It is not required, per the linked FAQ admissions section:

https://pe.gatech.edu/online-masters-degrees/analytics/faqs#...

--EDIT-- On the admissions criteria page, it states the following:

"5. Optional - Applicants may choose to submit standardized test scores, most commonly GRE or GMAT (but if appropriate, LSAT, MCAT, etc. scores may also be considered)."

So that may help get you in.

https://pe.gatech.edu/online-masters-degrees/analytics/appli...


It isn't required for the online MSCS at GT


Can anyone recommend a great and respectable ML online masters (assume cost not an issue)?


Stanford offers an online MS in CS using videos of the same courses that are offered on campus. So does Columbia, though their online course offerings seem to have decreased significantly in the past few years. Both programs cost about $5k/course.

I think both schools offer a track that emphasizes AI/ML, though I'm not sure more than a couple of their available courses are in those topics.


In the Georgia Tech OMSCS program you have to pick a specialization. Machine Learning is one of the options.


How is this different from the Udacity Georgia Tech Masters program?


It comes with the Georgia Tech brand name associated with it. College degrees are 20% content, 80% reputation and branding. For instance, if you want to earn $100k/yr, the way to do so with the least amount of effort is to attend a school with a great reputation. Reputation in academia has much more to do with faculty prestige and research, not actual academic rigor for students, but most companies find it far easier to trust the brand than build effective interview and recruiting processes. Ergo, brands matter.


Agreed. But if GT keeps offering more and more Master degrees this way, I can see them cheapening their reputation. It's a quick way for universities to make money, but at a cost of reputation.


Yes, to an extent, but as strange as it sounds, you can jeopardize your reputation with the companies that hire your graduates and still maintain your status as a prestigious research institution. I think the gamble GT is taking in this context is that this type of degree is terminal and largely self-directed, meaning the primary recipients will be self-educators who want it specifically for practical application. That means they are essentially just people who will learn and apply the material anyway, but they want the paper credentials to go with it. That reduces their risk.


I'm not sure pure numbers will be the issue. Whether GT grants 25 or 2500 MS degrees in Analytics is irrelevant; the quality of the graduates with that degree is what matters.

Provided they do not relax their standards, I don't see there being an issue. An MS appeals to professionals who are unlikely to relocate for a program. I'm in a suburb of NYC; if I wanted an MS, I'd have to consider commuting to Princeton or Yale, at an hour and a half to two hours each way, to the much closer NYU or Columbia but with similar travel times once the intersection of mass transit schedules and class times are considered, or to the state school 15 minutes away with a much less prestigious program.

Meanwhile, GT has a prestigious program at a cost comparable to or better than the state school, with no commuting issues. It's the program I'd go into, and I live close to a surfeit of prestigious CS programs! There are plenty of qualified applicants across the country that don't have the option of "drive to your favorite of the 3 nearby Ivies".

If they keep the admissions process and curriculum/evaluation equivalent between online and in-person, then going online greatly expands their applicant pool but doesn't necessarily dilute it. If the program decides to relax their standards to get even more money, then they'll have problems, but that strikes me as being penny-wise and pound-foolish.


Those who actually complete a full online course are probably great examples of self-motivated workers who will make the college look great.


Why? Unless they degrade the quality of contents and exams of course.


> Reputation in academia has much more to do with faculty prestige and research, not actual academic rigor for students

Also has a lot to do with selectivity. At the entry level, companies can rely on selective institutions to do some of the vetting for them.


Accreditation. Simply put, the Udacity course is just something you do, while the GT Udacity course is an accredited college course from a university whose accreditation and reputation stands behind the course.

One is a Udacity Certification, the other is an Accredited Georgia Tech Masters Degree.

"Udacity is not an accredited institution and we do not directly provide college credit. We have, however, partnered with Georgia Tech to offer an accredited, fully online Master’s Degree in Computer Science. While the courses are hosted on Udacity, the degree is conferred by Georgia Tech. Learn more about our Georgia Tech partnership"

https://udacity.zendesk.com/hc/en-us/articles/207991913-Can-...


He probably meant GATech's online MS done together with Udacity: https://www.udacity.com/georgia-tech


yes, I meant this


Not saying it is fair (maybe it is, maybe not), but the name "Georgia Tech" carries more weight on a resume.


It's another department jumping into the online delivery space. Looks like they're reusing a lot of the same policies that worked for the CS program. They are partnering with edX as Udacity's focus as a company has gone from university partnerships to their nanodegree model.


Just a heads up, but the GA courses on Udacity don't have any of the programming assignments anymore only the multiple choice quizzes and videos. They were removed when the OMCS program was introduced I think because GA wanted to use those assignments internally.


Does anyone know of an online mathematics masters degree?


University of Washington offers online MS in applied math. However, it's pricey.

Here's the link to it:

https://www.appliedmathonline.uw.edu


What a joke...


or... you just read, observe, learn, build, think, communicate, publish, for free, at your own pace, 24x7, etc.


Following the links on the program at the Georgia Tech Web site, the program looks like a fairly wide buffet from practical computing, current business applications, statistics, and operations research.

Georgia Tech is especially strong in operations research.

So, here data science is a new bottle of wine blended from some now quite well known old bottles of wine. And it is not nearly the first such blending since there have also been programs such as mathematical sciences and applied mathematics. Other blendings have included mathematical finance, financial engineering, and bio-statistics.

Apparently the high current interest is because now the associated computing is much cheaper, more powerful, and easier to use. And there has been a lot of hype from some sources.

However, I question if US mainline business is much interested: IMHO and my experience says that nearly any specialized technical material faces a serious obstacle since in the organization chart the highest ranking technical person (if not the CEO then necessarily a subordinate) has to report to a supervisor who knows from much less to nearly nothing about what that technical subordinate person is doing.

MD doctors, CPA accountants, licensed engineers, and licensed lawyers have some crucial, serious professional status, processes, support, etc. that is missing with applied mathematicians, statisticians, data scientists, etc.

For software developers, roughly, the solution is for the organization to have a CIO, all the developers are in the CIO's organization so report only to experienced developers, and only the CIO reports to, interfaces with, non-experts in computing.

Computing is now so darned important that the rest of the C-suite has to swallow their pride and accept the CIO at the table.

Net, I fear that data scientists will have too little professional or organizational protection from rain falling down the organization chart from the C-suite.

Or, for the supervisor, most projects will be lose-lose: If the project fails, then the supervisor has a black mark from wasting money on a failed project. So, with a failed project, the supervisor loses.

If the project is successful, then the supervisor and, maybe, everyone in the C-suite, maybe even including the CEO, can be afraid of the project leader now regarded as a 900 pound tiger and, thus, a loss for the C-suite.

Here the organization chart from the project leader up to the CEO is engaging in classic goal subordination, that is, pursuing what is best for themselves personally while sacrificing what is good for the company.

And for startups, what fraction of venture partners would be able to evaluate a proposal that makes heavy use of some of the more advanced applied math in that Georgia Tech program? Net, the venture partners don't know the technical material, either.

Or, as I suggested, nearly all wine in the blend is now quite old, and it didn't achieve much traction in mainline business.

My short summary view is that for such technical material, especially material more advanced than in the Georgia Tech program, and for a startup, the founder CEO needs to be both (A) the main expert in the technical material and (B) essentially a solo founder who can write the software, bring it to market, and get the coveted traction significantly high and growing rapidly -- at which time the founder may not be willing to accept equity funding and report to a BoD that does not understand the work, that is, be back in the situation of a technical subordinate reporting to a supervisor who does not understand the technical work and, with the low expenses of a one person company, just grow organically from revenue.

Or, IMHO, the most promising career future of an applied mathematician, etc., in business is to be a solo founder of a startup.


This is not news in the U.K.


I just wonder what the job prospects will be like for this. This is basically data science, a field being crowded rapidly by PhD's fleeing academia. With 3-month data science bootcamps, people are now saying expect 3-6 months to find employment, often as an entry-level data analyst. I expect the outcomes of the GT OMSA to be much better given the breadth and rigor of coursework, but who knows by how much? Also, while $10k tuition is low, the cost of lost income from pursuing this fulltime for 12 months makes it cost more than the 3-month bootcamps whose tuition usually runs $15k. If most OMSA grads find jobs right out of the program, versus 3-6 months of job hunting for bootcamp grads, the OMSA becomes a much better deal.

Edit: There is placement data for the on-campus program: http://www.analytics.gatech.edu/placement. 95% within 3 months of graduation, cohort size 21 students, with the majority (40%) taking an "analyst" title, average salary $100,000 (61% going to Atlanta, so this could be a little depressed compared to west coast tech salaries).


I would also be a bit hesitant about job prospects. My last job was at a large nonprofit in SF on their data team, and both my boss and my only non-contractor coworker were PhDs who fled academia. Salaries for the tech teams in general were 25-50% below market and overtime was high, and there were still PhDs taking these jobs.


EDIT: The awarded degree is the same (M.S. Analytics) as the "residential" program. The below assertions are false, but I have left the original comment intact for posterity.

-----

I laud continuing, online, and affordable education options, but this degree is still very much a second-class citizen. It is not the same degree that's awarded to "residential" students (that would be M.S. Analytics).

It's unclear whether the granting institution is Georgia Tech itself, one of the "collaborating" colleges (i.e., Scheller College of Business, the College of Computing, or the College of Engineering), Georgia Tech Professional Education, or even EdX.

All this affects the "value" of the credential.


>> It is not the same degree that's awarded...

False.

"How will this degree appear on my diploma and/or transcript? The name "Online Master of Science (OMS)" is an informal designation to help both Georgia Tech and prospective students distinguish the delivery method of the online program from our on-campus degree. The degree name in both cases is Master of Science in Analytics. The track designation does not appear on the diploma or transcript." [1]

[1] https://pe.gatech.edu/online-masters-degrees/analytics/faqs


Thanks for the correction, and I've updated my original comment to note the same.

Interestingly, I went looking for this information, including skimming that FAQ section. This disparity between online and traditional degrees awarded is common, so I'm surprised (or maybe biased is a better term) that GT uses this "informal designation" everywhere, including phrases like: "... Online Master of Science in Analytics (OMS Analytics) degree will be available..."


It may affect the "value" of the credential for the small set of resume readers who are up to speed and have a real opinion on it, but I would also think that the name "Georgia Tech", which has quite a legendary status in Georgia, affects that value more. A whole lot of people see "You have a degree from GT? That's what I like to see!" around here.

I would argue as a Georgia Resident that a Georgia Tech OMS Analytics would be viewed in higher regard than a Kennesaw State University M.S. Analytics (if they offered it, I know they offer other similar competing programs)


If anything GT is viewed better outside of the state than within it.

Few realize that a significant part of the reason that Georgia (for all its problems) isn't Alabama/Mississippi/South Carolina is because of GT and Atlantas rise from regional prominence to national and international recognition in technology, business and culture the last 30 years.

Never a prophet in your homeland and such.


>> It is not the same degree that's awarded...

This is just inaccurate and a falsehood.


>> It is not the same degree that's awarded

Very easy to disprove this. And as an OMSCS graduate I can tell you that at least the CS degree is not a second class citizen.

It's these sort of stereotypes, which have been reinforced by schools like Ashford and University of Phoenix, that we need to shirk. Online programs of this caliber enable the higher education of thousands who would otherwise not have the opportunity.




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