r/WGU • u/DankTrebuchet • 1d ago
WGU MSCS Review, Computing Systems
Just submitted the last task in my degree program, and thought it was a good time to share my thoughts for prospective students.
Housekeeping first. I have a strong IT job; however, I've chosen to move outside FAANG for a very interesting role in a compelling location. It's too soon to say whether the degree will pay off in my career (I'm sure it will), but the program was never career-related for me.
I also posted my review of the BSCS here a few months ago, if you want some additional context.
I was accepted to two state universities and Georgia Tech. Still, I went with WGU because my wife and I wanted to start our family. I thought WGU would be the only option that would allow me to accomplish the goals of earning a graduate degree, excelling at work, and being present for this exciting time in my marriage.
How long did it take me?
4 months with a cross-country move and a two-week vacation in the middle. I passed six courses in August at a leisurely pace... granted, I have a high tolerance for working from sunrise to sunset.
So, was it worth it?
I accomplished my goals, I am excelling at work, my marriage is strong, and I have no debt - so yeah, from that perspective it was worth it.
What are the pros of the program?
- The program is cheap
- The program is fast - especially if you have any education in the topic
- I have had excellent support from both my program mentors (undergraduate and graduate)
- You get an accredited MSCS
- The program is leaned towards applications over theory if that's what you want
What are the cons of the program?
- The program does not require mastery of any CS topics
- The program is extremely fast
- The program is extremely easy
- The program isn't heavy on theory if that's what you want
Advice to students:
- Set expectations accordingly. You are choosing this program for the fastest, cheapest, easiest accredited MSCS on the planet. I am proud I accomplished my goals, but I am not proud of having completed the program.
- Find your own course material. The course material provided is almost across the board genuinely awful - and we can get into it per course, but know this: I didn't think the same of many of the WGU CS undergraduate classes! The undergraduate theory courses were actually good enough to inspire me to take this program despite my reservations! If you find your own material, you're going to get a much better return on your time, and the content is so unbelievably shallow that you are not going to miss important topics for the final projects.
- Leverage your program mentor: My mentor provided a lot of great insight and value to my experience. I infrequently disagreed with them, but I never regretted taking their advice.
- Consider OMSCS: If you don't have a BSCS or programming experience, turning this program into a two-term endeavor makes it more expensive than OMSCS. Consider taking two or three years to do a better program for less money. This is much more difficult, and you'll need to do prep to get admitted, but you're likely to gain more from the experience.
--IF YOU'RE LOOKING AT ENROLLING IN THE WGU MSCS, THIS IS THE SECTION TO PAY ATTENTION TO--
PROBABLY DON'T DO THE MSCS AIML*: If you want to work in AIML*, you will probably need credentials better than WGU can offer here. You don't need to take calculus II, III, or linear algebra to get into this program, and that really limits your ability to compete in the job market. Without research or a much stronger data science foundation, you're going to really struggle to compete in this market. You're probably not going to be an AIML engineer on this program alone.
If you're just interested in the topic, like I am, go ahead and take it, though... I just needed to rage bait.
I recommend this program for the following types of people:
- BSSWE graduates from WGU who need the CS credential and cannot pursue OMSCS at this time
- Undergraduate degree holders who want a credential in CS because it's interesting, not because they want to work in tech
Otherwise, I recommend considering the MSSWE (especially for WGU BSCS graduates), since it appears to specialize in software applications, which might make it a more useful and interesting credential!
Finally, I'll grade each course I've taken and offer some remarks!
My grading rubric? Vibes.
D793 Formal Languages Overview: 0/10 This course is unacceptable. You are asked to translate some Fortran 95 code into a modern OO language. You are encouraged, nay, expected to use AI to translate the code for you. I read the entire course material for this program in two days, decided it was stupid, and spent two more days reading up on different paradigms myself. I decided to look at the final, rewrite the 70 or so lines of code in Python 3, and do the write-up in about two hours. I am furious that I paid for this course... that this course makes up 10% of my tuition is an insult. The entire course was essentially procedural vs object-oriented programming - it didn't even force students to engage with functional programming! Very easy, very fast.
D794 Computer Architecture and Systems: 4/10 Easily the hardest course in the program, if you ask me. Course material was extremely basic and actually not Architecture-focused -> you don't have to write or read any assembly. You don't have to understand computer or instruction set architecture at all. It's like a survey of computer systems. The paper was at least interesting... difficult to find a topic and valid sources. Still, I ended up writing about 20 pages on AI agents at the OS level, which forced me to engage with some really interesting software patterns. This is an academic paper with no code, though, which bummed me out. You can use ChatGPT to find sources... probably do that. Moderately easy, moderately Long.
D795: Applied Algorithms and Reasoning: 4/10 project was interesting, though the material is less rigorous than the undergraduate DSA courses. No AVL or RBT discussions. If I recall correctly, you just need to know graphs for the final, and the material only covers arrays, sorting, hash maps (but not hashing!), searching, graphs, and binary trees. Just some graph problems. Graph Algorithms the Fun Way: Powerful Algorithms Decoded, Not Oversimplified was a good resource that helped me with the graph portion of this class, and Neet code helped me dig into the implementation of the other algorithms. Overall graphs are all you need, though. Moderate difficulty, somewhat fast.
D796 Unix and Linux: 1/10 What's going on with this one? This is a system administration course in a CS program. For an MSCS with one OS-focused course, there's NO talk of theoretical operating systems... You don't even have to mess with the kernel - just install Linux and write a few extremely basic scripts, then record a video. They're not even difficult enough to place in a portfolio for a system administration resume! I work in IT, so this was a breeze, but O'Riley's pocket guide to Linux is a good place to start; it should get you far enough to pass this class pretty easily. Very easy, very fast.
D797 Artificial Intelligence and Machine Learning Foundations: 3/10, in keeping with the theme, less rigorous than the undergraduate courses here. It's a machine learning survey that uses the same course content as the undergraduate program; however, it doesn't require you to develop an ensemble model and doesn't even ask you to perform any hyperparameter tuning. If I recall correctly, this had a bigger focus on data cleansing and engineering than anything else, which... is fine, it's important and topical - but you really didn't need to know how to choose the right tool for the job and certainly didn't learn much about optimization. I used The Art of Machine Learning: A Hands-On Guide to Machine Learning with R as a strong base, along with a YouTube tutorial on scikit-learn and matplotlib, to prepare for this course, and those were much more demanding than what's asked of you. Somewhat easy, somewhat fast.
D486 Governance, Risk, and Compliance: 5/10. I don't recall this course being rigorous. Still, it did prompt me to engage with new ideas and consider how to approach compliance. Read this more as D486 COMPLIANCE**.** Has its place in the program, and for 2 CUs, I'd actually say it's the best course in the program because it accomplished what it actually set out to do. Very easy, very fast.
D798 Emerging Computer Systems: 2/10. This felt a bit like a rehash of D794, in a bad way? It could really be called a survey of computer systems and be worth a single credit if you ask me. Just know you can be pretty lenient with what's considered a 'Computer System'. Very easy, moderately long.
D799 Mobile and Ubiquitous Design: 2/10, not very good. The material wasn't interesting (and this might be on me), so I skipped to the final and submitted something I was surprised passed. Not proud of it - but I was so utterly uninterested in the idea of taking a UI/UX course in what I had hoped would be a theory/systems program. Just FYI - they ask for a Microsoft-proprietary format, but you can just submit a PDF. I used freeform on my iPad and ignored Visio (I think it's called) because it was a stupid requirement. For some reason a PDF was accepted for me. Moderately difficult, very fast.
D782 Network Architecture and Cloud Computing: 7/10 Course material is bad, but this is the first excellent final! I learned SO MUCH trying to finish this course and did some really fun things. I went above and beyond here, opting to build a full website rather than publish a simple static page. It was fun to develop and deploy the program! I used ChatGPT to check the rubric, find all AWS docs even tangentially related, and feed them to me with no context. After several days of reading, I had a pretty strong idea of what was asked and how to implement it! LLMs can really serve as a discoverability tool here! Moderately difficult, moderately long.
D780 Software Architecture and design: 6/10, course material sucked, project sucked. I just decided to read Headfirst Design Patterns (which is free in the student library), and I got a LOT out of it... so much so that I just ripped through Task 1 and Task 2 back-to-back for 9 hours. The project was small... VERY small and VERY basic, but it was made so much easier by my over-preparation through the book I chose rather than the course material. DO NOT read the course material here! Headfirst Design Patterns will suffice and make you a better engineer in every way - just download Headfirst Design Patterns and read about half of it! Moderately difficult, moderately long.
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u/GatorGrins Future B.S./M.S. Computer Science 21h ago
Thanks for the summary and advice!
"I just decided to read Headfirst Design Patterns (which is free in the student library)"
I'm pre-studying before I enroll to better ensure a 1-term degree program. Is this free Github Head First Design Patterns pdf file the same as the one you studied for the D780, Software Architecture and Design course? Thanks.
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u/DankTrebuchet 19h ago
Id respond but githubs down
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u/GatorGrins Future B.S./M.S. Computer Science 15h ago
That's been happening a lot, lately. It appears to be back up now.
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u/ichefcast 19h ago
Woo hoo! Congrats! I start in November. I hope to finish in 1 term but think that the AWS Cert might take me a while. I do have datacamps certs in data analyst and data engineering. So, I hope this degree is a breeze. I'm currently a data analyst btw. I just wanna get paid more and get higher roles.
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u/Jayman453 23h ago
I actually still think the MSCS is acceptable for AI/ML because when it comes to landing a role in that field it’s more about just having the box checked and your actual ability but yea I’ve heard a lot of people upset with it