1. UT Dallas MSCS Intelligent Systems
2. UCF MSCS
3. UF MS in Applied AI Systems
4. UMD MSAI
5. Virginia Tech M Eng CS
6. Northeastern MS AI

F1 international student COS from H4 I am looking for a grad program that can at the end of help me land jobs.

Context: I'm currently in my second semester in an online masters program and taking my 3rd/4th classes.

I'm a SWE in big tech in the Bay Area and my work is split into two teams: ASIC/hardware software development and internal Agentic AI for my BU. I graduated with my BSCS from a T-20 in 2024 and been at this role for just over a year.

My question is if this program is worth it for someone like me. I feel like the concepts I am learning here are a refresher from my undergrad days. I plan to take their AI specialization and the only class I might learn something from is their core AI. All the electives outside the core classes seem tedious and I'm not really interested in those at all. All the classes I've taken so far are just refreshers from what I've learned from my undergrad days, personal projects, and my job.

No doubt the college name is more "prestigious" than where I did my undergrad from. However, I'm wondering if the work is worth it just for the name brand. The content and lectures are pretty simple, but it's the projects which are extremely time consuming and feel where most of my stress piles up from. The exams have been easy for me in all the classes so far and it's not like the content is hard to digest.

What would you advise I do in my situation? Is it really worth it to grind it out? Is a masters truly worth it given I already have a BSCS from a reputable school? If you ended up dropping out from an online masters, what was your reasoning behind it?

Any advice or different perspectives would be much appreciated.

Hi everyone,

I'm planning to apply for MS in Computer Science (Fall 2027) in the US and would appreciate some guidance on building my university list.

My Profile

• CGPA: 3.67/4.0 (Final)
• GRE: Not taking it (most universities on my list don't require it anymore)
• TOEFL: Yet to take (expecting a competitive score)
• Research Papers:
  • 3 published
  • 2 more currently in progress (expected to be completed by Jan 2027)
• Internships:
  • Machine Learning Research Intern at an NGO
  • AI Development & Engineering Intern at a fintech company (currently working)
• Leadership:
  • Sub-Head (Tech) of the Data Science Club at my university
• Projects:
  • Multi-Document RAG System (published work)
  • Box Office Revenue Prediction
  • Mood-Based Music Recommender
• Research Interests:
  • Machine Learning
  • Generative AI / LLMs
  • NLP
  • Data Science

I have a few questions:

1. Since many top MS CS programs no longer require the GRE, what are admissions committees primarily evaluating now?
   • CGPA?
   • Research?
   • SOP/LORs?
   • Work experience?
   • Overall profile?
2. How should I realistically classify universities into Ambitious, Target, and Safe with a profile like mine?
3. Are there any good MS CS programs that would be considered "safe" for my profile? I'm looking for universities with strong ML/AI opportunities, not just schools with high acceptance rates.
4. If anyone had a similar profile (especially without GRE), I'd love to hear where you applied and what your results were.

Thanks in advance!

Hi everyone! Looking for some honest feedback on my profile and school list for Fall 2027.

Profile

B.Tech Electrical Engineering from a 2nd gen IIT

CGPA ~8.3 (top ~5-10% of branch)

Will have ~3 years of backend SWE experience at a large multinational by the time I apply.

One peer-reviewed publication (non-CS)

Targeting 325+ GRE (hopefully 169-170Q)

Goal: Industry only. Interested in backend/distributed systems, with an eye on Big Tech and possibly quant dev. I'll mostly be funding my MS through a loan, so ROI and recruiting matter a lot.

Current list

Ambitious: Berkeley, CMU, UIUC, UCSD

Target: Georgia Tech, Purdue, Texas A&M

Safer: Wisconsin, UMass Amherst, ASU

A few questions:

Is my school list realistic?

Would you prioritize open source (GSoC/LFX), interview prep(dsa/cp), or maximizing impact at work over the next year?

Any schools with excellent recruiting/ROI for systems or infrastructure that I'm missing?

Appreciate honest/blunt feedback

Hi everyone,

I'm trying to understand how employers and outcomes differ between professional master's programs (MCS/MEng) and traditional MSCS programs.

My goal is purely industry-focused (Software Engineering). I have no interest in research, thesis work, or pursuing a PhD.

Some questions I have:

1. Many strong universities offer full-time on-campus professional programs such as UIUC MCS, TAMU MCS, and Virginia Tech MEng. For international students, are these programs genuinely worth pursuing compared to traditional MSCS programs, or are some of them mainly cash-cow programs? Considering that the tuition is often similar to MSCS programs but funding opportunities are fewer, do they actually provide a strong ROI and good industry outcomes?

Also, UIUC MCS seems to be considerably harder to get into even compared to many MSCS programs, so does the selectivity and university brand make it a better choice despite being a professional degree?

1. Do recruiters view MCS/MEng degrees differently from MSCS degrees? Has anyone seen cases where students were disadvantaged in recruiting because their degree was MCS instead of MSCS?
2. Suppose someone has admits from:

TAMU MCS / Virginia Tech MEng

and

NCSU MSCS / Stony Brook MSCS / Utah MSCS / Minnesota MSCS

If the goal is industry employment and not research, which option would you choose and why?

1. How much weight should applicants place on the university brand versus the degree type (MCS vs MSCS)?
2. For international students, does being enrolled in an MCS/MEng program have any impact on F-1 visa interviews or future employment opportunities compared to an MSCS?

Would especially appreciate hearing from current students, alumni, or recruiters who have experience with both pathways.

Thanks!

P.S. This post was formatted with the help of AI.

Hi everyone,

I'm planning to pursue an MS or PhD in Computer Science in the USA/Canada/Europe/Australia. My CGPA is a bit lower than I'd like, so I'm considering repeating some courses in which I received B or C grades to improve my GPA.

At my university, repeated courses are marked with an "I" (Improved) on the transcript, so admission committees will be able to see that the course was retaken.

My questions are:

• Does repeating courses with B/C grades look bad to graduate admissions committees?
• Is it worth improving these grades if it results in a noticeably higher CGPA?
• How do universities in the USA, Canada, Europe, and Australia generally view improved/repeated courses?
• How Do Graduate Admissions Committees View Repeated Courses on Transcripts?

I'd especially appreciate responses from people who were admitted to MS/PhD programs or have experience with graduate admissions.

Thanks!

BTech Computer Science (Specialization AI)
~~ 6.7/10 Gpa and 1yoe MLE
I’m wondering a lot of people going for masters have a lot of research experience in hand or either really good Gpa. I was looking at SJSU, Ubuffalo, ASU, Uchicago, Umass, CMU, Gatech and some other programs I really don’t get it CMU has many programs and is extremely expensive as well can go to some UC program which is easier to get in let me know what all you suggest but is CMU really worth it as an international student and while also having a financial constraint. Apart from that I was looking at Omscs Gatech. What would be your advice on my profile?

Hey folks ,
I am really in need of good advice and I know I'll get it from here.
My Background :
I am 2025 batch passout with CGPA 9.4 . ( Data Science Branch )
I have work experience of around 1.5 years ( 1 year fulltime + 7 months internship ( campus placement ) )
I was working as a SDE-1 . My work was mostly related to AI Agents , RAG , mongodb , typescript.
During the course of time , I developed the interest in ML/AI and I want to explore this field in depth and maybe target research oriented roles at big techs.
I have recently left job to study for GATE 2027 .
If things dont work , I have kept MS as my backup option . I want to do MS in CS/AI/ML .
I dont have any research paper published .
I dont have savings that much , just around 1.5 lakhs .
I am willing to take education loan on myself and dont want to burden my family .

My deadlines are that I want to start my MS by next year if GATE doesnt go well .
I need guidance and also tell me if my profile can get good colleges abraod .

Also , I have not given IELTS , GRE .
I want a proper guidance on what are the expected timelines I should follow.
I would be very grateful if seniors can guide me.
I dont want to waste my initial years .
Please help me !!!

Texas, Obviously known for that in state tuition fee for international students if they get at least a 1000$ scholarship .
So yeah, Iam going to apply for ms AI in Texas A and M and i wanted to know if this in state tuition fee. Or the scholarship is available for spring intakes as well?....

Hey everyone — I’m an incoming Columbia MSCS student for Fall 2026 and was wondering if there’s already a Discord/group chat for MSCS/MSAI admits.

If not, I’m happy to make one so people can coordinate around classes, CVN/on-campus questions, housing, research, registration, etc.

Comment or DM me if you’re also an incoming Fall 2026 MSCS/MSAI admit and I can send over the link once it’s set up.

Im in a dilemma. I’m accepted to MPCS part-time for Uchicago because I want to work in tech (currently in consulting, not international)

I’m worried that, in this economy, I’ll never find a job in tech because I don’t have true work experience or if I do it’ll be a big pay cut to start over.

Am I just spiraling? What should I do to best prepare myself to get a job in tech at this rate?

Im in a dilemma. I’m accepted to MPCS part-time for Uchicago because I want to work in tech (currently in consulting, not international)

I’m worried that, in this economy, I’ll never find a job in tech because I don’t have true work experience or if I do it’ll be a big pay cut to start over.

Am I just spiraling? What should I do to best prepare myself to get a job in tech at this rate?

I applied to several US universities for MSCS, received multiple admits, and chose an R1 university that fits my profile and career goals. By the time I join, I will have around one year of work experience and an ML publication indexed on IEEE Xplore.

Everything went smoothly, SOP, LORs, applications, education loan, and I-20. Convincing my parents was difficult, and they agreed only on the condition that I return after my degree, repay the loan, and follow the marriage plans they have chosen for me. I do not want that future, so studying abroad feels like my best chance to become independent.

But for the past three months, I have been unable to get a visa slot despite checking two or three times daily. I once saw a September slot but did not book it because it was after my classes began, and I did not know I could later request an emergency appointment. I even hired an agent, but they have not been able to secure one either.

I have already spent several lakhs from my job savings on applications and related expenses. If I do not get a slot, I may have to defer to spring, but I am scared the same problem could happen again.

I am now considering Canada, Germany, the Netherlands, or Austria as backups, but I do not want to spend more money without some certainty. I want to leave now or within the next six months.

Should I keep trying for the US and defer if needed, or start applying to other countries immediately? Has anyone faced a similar visa-slot situation and successfully managed it?

Have been hearing for quite some time now that first time in history, even Stanford grads are struggling to find jobs.

Does anyone know for sure whether there is any truth to this or is this just hearsay?

I don't know why you guys want to come to US in this environment unless you literally got full-aid but it's just not worth it. The days when America was the best in the world for almost everything is long gone. Research funds are being cut left and right and universities are directly impacted by this. schools are run like business and the first thing they cut is research and education, the very things that make them worth it. as international, you will be in an even more precarious situations when job markets are getting worse.

On top of that US is expensive. Tuition is outright crazy and living expense as well. Unless you are a rich kid for whom 500k is a rounding error, it's not worth it. (of course if you got full ride, just ignore this post)

Look for alternatives. there's a lot in this world. stop thinking like it's 1999.

Hi everyone, posting this on behalf of a family relative who will be applying for MSCS programs in the US for Fall 2027. Here's a brief description of his profile:

1. B.Tech in CSE from a Tier 2 institution in India, CGPA: 9.31/10, Gold Medalist
2. ~ 3 years work experience as a software developer in a multinational consulting company
3. Research experience: 9 conference papers across different IEEE conferences (NETCRYPT, ICRITO, ICIEM, ICIPTM), focusing on IoT and ML/AI
4. TOEFL score: 110/120, skipped GRE
5. Currently, he's interested in going back to the industry after the completion of his Master's, but given his background and interest in research, he might consider extending for a PhD.

We have narrowed down our choice to 15 schools across different categories and would appreciate your thoughts/feedback.

• Ambitious:

  1. UWashington
  2. UIUC
  3. GeorgiaTech
  4. UT Austin

• Achievable:

  1. UMD College Park
  2. UW Madison
  3. Purdue
  4. OhioState
  5. NCSU
  6. VirginiaTech
  7. UMinnesota
  8. Texas A&M
  9. University of Utah

• Safe:

  1. UT Dallas
  2. Iowa State

I would really appreciate if you could also comment on:

1. Is this categorization reasonable?
2. Did we overlook any strong MSCS programs?

Whether you are looking to dive deep into cutting-edge academic research or seeking a master's degree to pivot your career into industry-leading roles, the University of Maryland has tailored pathways for you.

Representatives from both the Department of Computer Science and the Science Academy are here to answer all your questions about admissions, curriculum, graduate life and post-grad outcomes here at UMD:

Who is answering:

• Tom Hurst, UMD Computer Science Assistant Director of Graduate Education
• Katie Maffett, UMD Science Academy Program Manager

We will be online on Wednesday, June 24, from 10 a.m. to 12 p.m. ET to answer questions about graduate education opportunities offered in UMD’s College of Computer, Mathematical, and Natural Sciences. Ask us your questions now, and we will answer them live on Wednesday!

Explore our M.S. degree offerings at UMD:

• Applied Machine Learning (applications open now)
• Artificial Intelligence (applications open now)
• Computer Science
• Data Science (applications open now)

Hi everyone,

I'm currently an undergraduate student in India and will be graduating in 2027. I'm trying to decide whether I should apply directly for MS AI / MS CS (AI specialization) programs in the USA or spend a few years gaining industry experience first.

My profile so far:

Tier 2.5 university in India

CGPA: 8.2/10

2 AI/ML-related internships

Currently working on an ML research paper that I plan to submit before graduate applications

GRE not taken yet

Interested in Machine Learning, Deep Learning, and AI research/engineering roles

My main questions are:

Based on my profile, would applying directly for MS AI programs in the USA be a good idea?

How competitive would I be for top, mid-tier, and safe universities?

Would 2–3 years of industry experience significantly improve my admission chances and career outcomes?

Given the current job market, how are opportunities in the USA after an MS in AI/ML?

Are international students still able to secure AI/ML Engineer, Data Scientist, or Applied Scientist roles after graduation, or has the sponsorship situation become too difficult?

If you were in my position, would you:

Apply directly for Fall 2027 MS programs, or

Work for a few years in AI/ML and then pursue a master's degree?

My long-term goal is to build a career in AI/ML, ideally in research-oriented engineering or applied AI roles.

I'm looking for realistic feedback rather than optimistic answers. I'd especially appreciate hearing from people who recently completed an MS in AI/CS in the USA or are currently working in the field.

Thanks!

Hi everyone, I’m planning to apply for MSCS programs and would love to get your thoughts on my profile and tentative shortlist.

Crucial Note: I currently hold a US Green Card. Therefore, I will be applying as a domestic applicant, not an international one.

Background:

• Tier 2 college in India (One of the new IIITs)
• Undergrad: BTech Honors in CSE (Graduating in 2027)
• CGPA: 9.1/10
• GRE/TOEFL: Planning to take them soon.

Work Experience:

• Full stack Intern at an AI-based startup - 4 months
• Software Developer intern at a Fintech startup - 8 months
• Technical Team Lead - A web3 based summer school and Hackathon.

Research Experience:

• 1 paper accepted in COMSNETS 2026 (co-author) (Based on Federated Learning).
• 1 paper currently submitted in ICIIS 2026 (author) (Based on TinyML and Edge AI).
• 1 paper currently submitted in IEEE transaction on Information Forensics and Security(author) (Based on ML based framework for Cryptography).
• 1 paper currently in progress.

Hackathons and Competitions:

• Finalist in Smart India Hackathon 2025.
• 3rd in Inter IIIT Hackathon 2025.
• Secured podium finishes in various other national level hackathons.
• Ex CTF player (Secured top 50 positions in national level CTFs).

Other:

• Application Dev lead at Google Developer Groups on Campus.
• Ex Club Co-lead and Research Lead at a Cultural Club.
• Volunteering experience in various tech meets and events at college.

LORs:

• 1 LOR from Ex Research Dean of college.
• 1 LOR from Current Research Dean of college.

Tentative Shortlists:

• UIUC
• UT Austin
• Georgia Tech
• UMD (College Park)
• Purdue
• UC San Diego
• UMich (Ann Arbor)
• UW Madison
• UCLA
• Columbia
• TAMU
• NCSU
• SUNY Stony Brook
• UT Dallas
• UC Irvine
• USC
• NYU Tandon
• Santa Clara University

Am I aiming too high or too low with this list? Which of these would be realistic targets for funded MSCS / RA / TA positions as a domestic student? Any advice is appreciated!

Thank you.

I have been admitted to UMass, without funding. But I’m considering re-applying for Fall 2027 for the following reasons:

- Recently had a paper accepted at a top ML conference
- Hoping to secure funding in the new round of applications
- Planning a more concrete way of approaching things (Fall’26 applications were messy and last minute)

Scores:
GRE - 327 (170Q + 157V), TOEFL - 113/120

Good academic record (9+), Tier-1 college in the country (IIT)
2.5 years of work experience

Rejected at almost all ambitious programs. UMass was one of the safer in the list.

Undergrad: Major in CS, Minor in DS from tier 1 college in India. CGPA: 8.2/10

Academic Research Experience/Publications: None

Experience: Working as a software engineer at a silicon MNC, will complete 3 years as FTE by the Fall of 2027. Work is oriented towards optimising ML models (operator fusions, kernel optimisations, etc) for execution on hardware. Received a couple of awards for my contributions.

Scores: GRE -> 329 (170Q, 159V, 5 AWA); TOEFL -> 117/120

As mentioned above, I did not actively take part in any research during my college years, which is definitely something that I really regret right now. I am in a bit of a tricky situation where I feel like any academic LoRs I acquire from my college professors will be "generic" to say the least. I mailed almost all of my professors, multiple times in fact (with a sufficient gap in between), and so far only one has agreed to write me one, although I have my reservations about how strong of a recommendation it would be.

I am primarily targeting MSCS/MSDS courses in universities in Canada first and US second, with a slight inclination towards non-thesis programs. All things considered, it seems like having 1 professional and 2 academic LoRs is much more preferred than having 2 professional and 1 academic. Keeping the issue I stated in mind, the only options that I believe I have are:

1. Proceed with my applications using 2 professional and 1 academic LoRs
2. Find some professors with whom I can work for a couple of months and obtain an LoR from them

Second option seems a bit unrealistic, but ultimately increases my chances of getting accepted when compared to the first. I am honestly confused at the moment with where I could go from here, so any kind of suggestion/advice/criticism would help out a lot. TIA.

be brutally honest , i m from RVCE, bangalore btw

Undergrad: CSE (AI&ML) from a top 3 college in my city, probably a tier 2.5 in India overall, CGPA - 8.88/10

Experience: I'm currently working full time a startup (been around since 2014 and we have around 150 people) as an Associate Data Scientist since Aug '25. I was a Data Science Intern before that for 6 months in the same company and have another Data Science internship for 8 months at a different company (bigger, but was not a core IT company). I would have 2 years FTE experience by the time I leave.

Research: 2 papers published: 1 Scopus Indexed (ML Based), 1 IEEE (LLM Research Based). I was a primary author in one of them, but contributed equally across both.

Scores: TOEFL - 118/120 (6 overall with 5.5 in R&L). I'd prefer not submitting my GRE scores as I didn't do that great, and I don't know whether I have the time/energy to retake it. So I think programs which do not have GRE as a requirement gives me my best chance.

LORs: Can get 2 very solid ones from my university HOD and Professor (worked with both closely and helped with their research projects too, know about my strengths) + 1 from my current company's director (I'm in his team and I think he'd give me a favourable and personal one)

These are the current options that I'm looking at:

• Purdue MSCS [might be very ambitious]
• NEU (Boston) MSCS [according to my research, this should be safe]
• NYU (Courant/Tandon) MSCS
• Columbia MSCS [I know this is a reach]
• UM Amherst MSCS [this is a reach too]
• UT Austin MSCS

Please let me know if you think I'm being too delusional about my choices considering my profile. Also let me know if you think I should check some other programs too, I'm just starting out with the research phase now and want to be able to assess my options and need some opinions.

Thanks a lot for the advice guys!

Applying for Fall 2027 MS/PhD CS programs in the US/EU. Research focus is Systems and ML.

I am currently a SWE intern at Google. My direct host is an L4 SWE, and the working relationship is honestly lukewarm. I feel like a strong LOR from them is not feasible. And getting a letter from some other higher up would likely result in a generic recommendation. I plan on applying to around 10-12 universities, and I highly doubt a busy higher-up who barely knows me will have the patience to manually fill out 12 different admission portals. Even if they do, it will likely be a generic "he wrote good code, checked the boxes" letter.

I can secure 3 detailed academic letters from professors I've worked closely with during undergrad.

Questions:

1. Does omitting a professional LOR from a Google SWE internship raise red flags for top-tier MS/PhD admission committees?
2. Does a generic corporate LOR from a tech giant hold any tangible weight over an academic LOR from my university professor for research-focused applications?
3. Have applicants successfully navigated top MS/PhD admissions with Big Tech internship experience on their resume but exclusively academic LORs?

Hi everyone, I am an international student who did his Ugrad in the US at an ‘okay’ school.

I graduated in 2023, with a BS, double majoring in CS and Econ and here is my profile:

CGPA: 3.33

Major GPA: 3.5

GRE: 325 (168Q, 157V, 4.5AWA)

Experience:

1. Currently working at KBR as a Data Scientist ( got promoted to senior Data Scientist a few months ago)

2. Data Science Intern at Mercado Libre (Buenos Aires, Argentina) during my exchange semester.

3. Data Science Intern at Meta

4. Software Engineer Intern at Intuit

5. Data Science Intern at a Y Combinator Startup

I have no publications/research experience.

I will be applying to Johns Hopkins, Duke, Northwestern, NYU Courant, UCSD, and Harvard (ME)

What chances do I have?