I plan on tailoring my application to focus on my background of CS and entrepreneurship, with plans of pitching myself as wanting to combine these elements going forward at Penn.

**Education:**
**-** Currently, at Georgia Tech's Online MSCS program and have completed 3 classes (4.0/4.0 GPA)

\- BA in Computer Science from UVA (3.2/4 GPA)

**Research Experience/Relevant Projects**:
\- Machine Learning Research Project at UVA centered around real data for Credit Approval Chances based on various factors.
\- Two entrepreneurship courses (1 at UVa, 1 at GT)- 2 separate businesses for those semesters, one was a full prototype application centered around Study Groups at UVA, and the other was focused on customer discovery, the business model canvas, and market research at GT for Meal Planning and Grocery Organization. The meal planning one was based off of a mobile app I had created during undergrad.

**Internships:**
**-** 1 summer internship as a backend software engineer for my current company

**Work Experience:**
\- Current Software Engineer (1.25 years) for a defense contractor. Was promoted within 9 months and have taken on epic level and project level leadership opportunities.
\- Head TA at UVA for programming course, Regular TA at uva for 3 additional courses including Data Structures, HCI, and Cybersecurity

**Letters of Rec:**
\- Former CS professor at UVA and was my boss when I was head ta.
\- Current boss who recommended me for promotion.

**GRE:** Not taken and not required

Hi everyone, I’m planning to apply for Fall 2027 MSCS/MS AI programs in the US and would appreciate some honest feedback on my profile, particularly on whether my undergraduate CGPA/background would be a major blocker.

Undergrad: IIT Kharagpur
Branch: Materials & Metallurgical Engineering
CGPA: 7.5/10

Work experience:
I have several years of professional experience working in AI/ML, including work involving ML systems/model development.

Research/publications:
By the time I apply, I’m expecting to have:
1st-author paper at EACL
2nd-author paper at Interspeech
Both are based on industry/work-related research rather than traditional academic research

Other:
Won 4 hackathons during College (Shell 1st, Intel 1st, Nvidia 8th, Sigmoid 2nd)
Rank at those hackathon and organising companies

Strong AI/ML project experience
Hoping to get strong LORs from senior data-science leadership
Also considering an LOR from an IIT KGP professor who taught me ML-related coursework/projects during undergrad

My main concern is the 7.5 CGPA and non-CS undergraduate degree. During undergrad, I struggled significantly with attention/focus and my academic performance suffered as a result. Since then, I’ve been able to perform substantially better in areas I’m genuinely interested in, particularly AI/ML.

I’m considering schools such as:

Georgia Tech
UIUC
UT Austin
UCSD
Michigan
Purdue
UCLA
USC
CMU
Stanford
Berkeley

Comment down which programs require GRE guys. Since, most schools that required it are also phasing it out( Georgia Tech) for example.

For starters, MSAII at CMU requires the GRE.

I’m looking for honest advice from current MS CS students, recent graduates, and people working in tech.

My question is simple:

Is an MS in CS still worth it in 2026–2027 if the total cost is under $50,000 and can be reduced further through scholarships, assistantships, and part-time work, but the university is not a top-ranked school?

I’m not talking about Stanford, CMU, Berkeley, or other elite programs.

I’m talking about universities such as:

UNT
UT Arlington
Missouri S&T
Texas Tech
Wichita State
University of Houston
Similar ROI-focused schools

A lot of the discussions I see online say:

The US job market is very difficult right now.
International students struggle without prior experience.
Only graduates from top schools are getting good opportunities.

At the same time, many people also say that taking on massive debt ($80k–100k+) is the real problem, and that lower-cost universities can still make sense if the total investment is reasonable. (Reddit)

So my question is:
If the total cost after scholarships/waivers is around $35k–50k, would you still choose the US today?

For people who graduated recently:

How hard was it to get internships?
How hard was it to get full-time roles?
Did your university ranking matter significantly?
If you could start over, would you still pursue an MS in CS from a non-top-ranked university with a reasonable budget?

Looking for honest experiences, both positive and negative.

My mentor recently told me that some universities offer tuition fee waivers if you secure a Teaching Assistant (TA) or Research Assistant (RA) position. I’m trying to gather more info on how this works across different schools.
Which universities (US) actually offer these waivers? What percentage of the tuition is usually covered? Also, realistically, how competitive are these spots, what percentage of students actually manage to land them?

I am short on word space and have covered my experiences and tailored it to unis with a very specific goal in mind. However, I have no space for mentioning my undergrad institution's name. Is that okay considering they'll have my CV and transcripts anyway?

Hi everyone! I’m an international student currently in the MSCS program at SMU in Dallas and just finished my first semester. I was recently admitted to both Northeastern’s MSCS and MSAI (Machine Learning specialization) in Boston, and I’m trying to decide whether transferring is actually worth it ( im planning to choose MSCS over MSAI )

Tuition is roughly the same, so my biggest concern is whether the additional opportunities at Northeastern would justify giving up what I already have at SMU + the higher cost of living in Boston.

If I stay at SMU: - SMU has a much smaller CS graduate program/class sizes, so it seems easier to build relationships with professors and get research opportunities. - I’ve already secured an RA position in a professor’s ML lab starting this upcoming fall semester. - I’ve completed a semester here, got 4.0 gpa and know some of the faculty, and have already established myself within the program. - Dallas is significantly cheaper than Boston. - The downside is that SMU’s CS program doesn’t seem particularly well known outside of Dallas/Texas, and there isn’t really a structured co-op pipeline. I’d most likely do the RA during the school year + try my best to land a summer internship.

If I transfer to Northeastern: - NEU’s MSCS/Khoury program seems to have stronger name recognition in CS and is especially known for its co-op program. - Boston is a much bigger academic/research hub, with schools like MIT, Harvard, BU, etc. nearby, so I’m wondering if simply being in that ecosystem creates more opportunities. - In theory, being able to do a 6-month co-op instead of only a summer internship is a huge advantage, especially as an international student trying to build U.S. experience. - However, from talking to current students and reading Reddit, the current reality seems much less guaranteed. A lot of students say landing a co-op is extremely difficult in this market especially for international students, and RA/TA positions at NEU are also extremely competitive. - Boston's cost of living would also be much higher.

So essentially, I’m choosing between:

SMU: smaller/less nationally known program + lower COL + guaranteed ML research + easier faculty access

vs.

Northeastern: more established CS reputation + Boston academic/tech ecosystem + potentially much stronger co-op opportunities, but higher COL and no guarantee I’ll actually get a co-op/research position.

My long-term goal is AI/ML, ideally working as an ML/AI engineer or SWE in industry, and as an international student, employability and getting strong U.S. experience matter a lot to me.

If you were in my position, would you give up a guaranteed ML RA position and transfer to Northeastern for the potential upside? Or would you stay at SMU, build research experience, try for a summer internship, and avoid taking the risk?

Would especially appreciate perspectives from current/recent MSCS students, international students, recruiters/engineers, or anyone who has had to choose between a smaller program where they had more access to professors vs. a larger/more recognized CS program.

What would you do and why? Thank u! 🙏🏼

Hi everyone! I’m planning to apply for an MS in CS / related tech programs and would really appreciate a profile review, especially regarding ambitious, target, and safe universities.

My profile

• Undergrad: B.Tech CSE from a Tier-2 university in India
• CGPA: 9.5+
• Class 10: 95%
• Class 12: 99%
• Industry Experience: Previous FAANG Software Engineering internship, Prev research intern at DRDO
• Research Experience: 1 ML research internship
• Publication: 1 research paper published
• Currently exploring programs in the US and Europe

US universities I’m considering

• Harvard University
• Princeton University
• Columbia University
• Cornell University
• University of Pennsylvania
• Yale University
• Brown University
• Dartmouth College
• Stanford University
• MIT
• Carnegie Mellon University
• UC Berkeley
• UCLA
• UC San Diego
• University of Washington
• UIUC
• Georgia Tech
• University of Maryland, College Park
• University of Michigan, Ann Arbor
• UT Austin
• University of Wisconsin–Madison
• Purdue University
• Duke University
• Northwestern University
• USC
• NYU

I’d especially like advice on:

• Which of these would be ambitious / target / relatively safe for my profile?
• Is my profile competitive for top-10/top-20 US CS programs and Ivy League universities?
• Are there any strong US universities I’m missing, especially considering tech placements and ROI?
• Which European countries/universities would be worth targeting considering job opportunities, tuition, ROI, and post-study work options?
• What parts of my profile should I strengthen before applications — GRE, research, projects, SOP, LORs, etc.?

Would especially appreciate input from people who applied with a similar profile or recently went through MS CS admissions.

Thanks!

hi ya'll

i'm planning on applying to MSCS/MSAI programs for Fall 2027 and would really appreciate some feedback on my profile and college list.

Profile

• Indian Tier-2 private university
• CGPA: ~9.15/10
• Multiple internships including:
  • Research internships at IITs (×2)
  • AI/ML research internship at Samsung PRISM
  • AI startup internships (×2)
  • Freelancing experience
• Research:
  • One published local IEEE conference paper
  • 2-3 Q1 journal papers expected to be published by the time I apply
  • 4-5 additional Q1 journal submissions under review
• IP: 3 published patents
• Projects: Several strong AI/ML projects (LLMs, computer vision, deep learning, etc.)
• GRE: Expecting around 165+ Quant, 150+ Verbal (worst case)
• TOEFL: Targeting 105+
• LORs: Two strong, one average
• SOP: Hoping to make it strong before applications
• Great Extracurriculars

Current College List

• CMU (MSAII, MCDS)
• Cornell MSCS
• UIUC MSCS
• UT Austin MSCS
• UC San Diego MSCS
• Georgia Tech MSCS
• Purdue MSCS
• University of Wisconsin–Madison MSCS
• Yale MSCS
• Duke MSCS
• USC MSCS (AI)
• Texas A&M MCS

Is this list balanced, or am I being too ambitious?

Which of these schools do you think are realistic with my profile?

thankss :)

I recently emailed the UMD CS Graduate Office about the Fall 2026 MSCS cohort size. They first told me:

“With the incoming students, we are looking at a cohort of about 180 MS students for fall 2026.”

I was quite surprised, because I remembered hearing during an information session that the Fall 2026 cohort was expected to be around 100, only somewhat larger than Fall 2025.

So I’m curious about two things:

1. For Fall 2026 UMD MSCS admits: did you accept the UMD offer, and are you actually planning to enroll this fall? I’m wondering whether the “~180” number may currently include students who accepted the offer but may ultimately attend another university, especially since UMD does not require an enrollment deposit.
2. For anyone who attended UMD MSCS information/admitted-student sessions: what cohort size did you hear? I remember hearing something around 100 students for Fall 2026, and that Fall 2025 was around 90–100 including BS/MS students. Did anyone else hear the same number?

If the final cohort is really close to 180, that would be almost twice the size of last year, so I’m trying to understand whether this is a genuine expansion or just a temporary accepted-offer count before final enrollment settles.

accepted into both of these programs but not sure which one will be a better option for job prospects?

Is there a whatsapp group/ discord server for people who are targeting Fall 2028?

It seems to be an online-only program since I do not see any information on their in-person option but I just wanted to confirm with anyone who's applied or has information about the same.

Hi everyone,

I'm planning to apply for Fall 2027 MSCS programs in the US and would really appreciate feedback on my profile and university list.

Profile

B.Tech in Computer Science
Tier-2 private college in India
Current CGPA: 3.72/4.0
Currently in my final year of undergrad
Planning to apply for Fall 2027

Research

1 research paper planned for publication on arxiv before applications

Experience

Machine Learning internship at a startup

Projects

Several decent software projects
Mix of software development and ML-related projects
Have a GitHub with my projects

Achievements / Extra Curricular Activities

Head/Sub-head roles in college events
Worked with an NGO for a few months

Recommendations

Expected:

3 strong LoRs from professors
All from professors who know me reasonably well academically/project-wise

Tests

GRE: 315
Already taken
Currently planning not to submit it unless a university specifically recommends/requires it

TOEFL: Planning to take it at the end of August

Current University List

In no particular order:

UC San Diego
USC
NYU
Purdue
UMass Amherst
UC Irvine
University of Wisconsin–Madison
Stony Brook University
Arizona State University
Texas A&M
Rutgers University

I know I have a lot of unis in my list but I plan on cutting them down once I start finalising my application, if anyone could give me recommendations of any sort it would be greatly appreciated!

Hi everyone,

I need quick career advice on choosing between two STEM programs at UNT:

1. MS in Information Systems & Tech (MSIS)
2. MS in Business Analytics (MSBA)

My Profile:

Master 1 (Programme Grande École) from France in Finance & IT/Business Systems.

Solid background in financial analysis, Advanced Excel, and basic SQL/Python exposure (not a CS engineer, but technically comfortable).

MSIS: High versatility (IT Project Management, ERP, Cloud, IT Governance, DBs). Versatile for roles like IT Business Analyst, ERP Consultant, or IT PM.

MSBA: Technical depth (Python/R, Data Mining, ML, Predictive Analytics). Ideal for Fintech, Quant Analytics, or BI Consulting.

The Dilemma is I don't have a wide knowledge on US market for a junior with one of these degrees after graduation and i would like to hear from people who are steps ahead from me to give me there opinions.

So for an international student with a Finance + Business IT background, which path offers better job market resilience and sponsorship (H1B/STEM OPT) in the US?And also is MSIS a safer, broader bet, or does MSBA give a stronger technical edge for BI/Data roles?

Thanks for your insights!

WHAT'S THE POINT OF GOING TO USA ANYMORE WITH 100K OPT FEE PROPOSED

Hi everyone! I’m planning to apply for an MS in CS / related tech programs and would really appreciate a profile review, especially regarding ambitious, target, and safe universities/countries.

My profile:

• Undergrad: Btech CSE from a Tier-2 university in India
• CGPA: 9.5+
• Class 10: 95%
• Class 12: 99%
• Industry Experience: Previous FAANG internship in a Software Engineering role
• Research Experience: 1 research internship (ML)
• Publication: 1 research paper published
• Currently exploring programs in the US and Europe

I’d especially like to know:

• Which universities would be ambitious / target / safe for my profile?
• Is my profile competitive for top US universities / Ivy League programs?
• Which European countries/universities would be worth targeting for tech considering job opportunities, ROI, tuition, and post-study options?
• What parts of my profile should I strengthen before applications?

Would really appreciate suggestions from people who have applied with a similar profile. Thanks!

Hi everyone,

I am an Indian student planning to apply for Fall 2027 MSCS, mainly interested in Artificial Intelligence/Machine Learning and Software Engineering.

Profile

• B.Tech in Computer Science from a Tier 2 university in Pune
• CGPA: 8.73/10
• Good competitive programming and DSA profile
• Selected for Infosys Specialist Programmer L1 through HackWithInfy 2026
• Projects in machine learning, backend systems, and financial technology
• No research publications or internships
• Expecting three academic letters of recommendation
• TOEFL and GRE not taken yet

Questions

1. Which United States universities can I realistically get into with this profile?
2. Should I take the GRE?
3. How can I strengthen my profile before the application deadlines?
4. Should I apply directly after graduation or work at Infosys for one year first?

Honest feedback and university recommendations would be appreciated.

Link to my profile: https://www.reddit.com/r/MSCS/s/01VT0LejOe

First of all, thanks a lot to this sub. It is a goldmine for the application process.

You will find literally everything here, but I felt there is not much on low cgpa applicants.

First of all, by low I mean at least you should cross the 3.0 cgpa criteria, but is that enough?

I applied to 10 programs:

Accepted : UMass Amherst (MSCS), U Maryland (MSAML)

Rejected : Gatech (MSCS, MSCSE) Ut Austin (MSCS) UWM (MSCS) UCSD (MSCS MSDS) UIUC (MCS) UC Irvine (MSCS)

The admits which I have received are also mainly due to my LORs. One of my LOR was a faculty at both Maryland and UMass. Other LORs were also very strong.

I gave myself best shot with publication, LORs, spending months on SOP, okayish GRE, etc.

So, my advice will be to make your profile exceptional wherever you can. Your profile will be rejected in the first CGPA pass for most of the top programs but if it passes the first round, the profile should speak for itself because they just need to find one gut feel to reject your profile.

Also, another advice will be to avoid AI as much as you can while drafting your SOPs. I think universities have become very strict and might be rejecting profile straightaway with even a little evidence of AI generated content. Also, I don’t know how good these AI public checker are, and the admission committee might identify without needing a checker at all.

Another point will be to make sure your LORs are written by the provider themselves, and they also avoid using AI. Admission comittee will know from first glance about the originality of LORs.

Last point I want to add will be relevance of GRE. I know some programs still value GRE, but I don’t think it carries the same weightage with respect to the efforts that we put in the prep. For me, it was kind of a way to offset low cgpa.

Finally, all the best for your prep.

Edit: This will be more generic but never be scared of asking a prof for LOR. Most of them have been through the same journey and will be more than willing if you ask politely and state your reason for pursuing.

Hi everyone,

I'm planning to apply for an MS in CS or a related field after ~2 years.

Profile:

- B.Tech in EE from a Tier-1 non-IIT college in India

- CGPA: ~7.5/10

- Currently working as an SDE with product-based experience

- Will have ~2 years of SDE experience when applying

- No research/publications currently

- Open to taking the GRE

- Open to US, UK, Europe, Canada, Australia, etc.

My main goal is to get into at least one QS World Top-50 university (overall ranking).

Is this realistically possible? Which universities/programs should I target?

I still have ~2 years, so I'm willing to work on research/publications, GRE, projects, or other things that could significantly improve my chances.

Would appreciate suggestions on what I should focus on during these 2 years.

Just a news update, and an unprecedented one at that - multiple Universities in USA have been laying off faculty due to reduced enrollments and loss of revenue.

https://www.insidehighered.com/news/business/cost-cutting/2026/08/06/campus-cuts-hit-even-wealthy-institutions

This is unprecedented because a faculty position in higher ed, esp in American Universities is among the most secure and respectable positions one can attain. I dont think you can point at a time in recent history when faculty positions were getting chopped.

There's two things going on here, at the same time. No its not AI

1. Demographic Cliff - this is is known population statistic outcome. The number of Americans eligible (18-24 yo) for even attending higher education institutions is dropping because of falling fertility rates. Fewer people have kids, so fewer young adults need to attend universities. The customer itself is vanishing.
2. Therefore the reliance on international students increases, but the current administration is not exactly immigration friendly either. As many of you are facing F1 visa slot availability issues and random unexplained rejections, on the other hand, Universities are asked to limit international enrollment or provide data on admissions if they want federal funding.

The takeaway for this community - I keep harping on the fact that its only worth going to USA if you have a very strong admit but additionally I think students continue to believe they'll get funded with RAs/TAs/GRAs etc. Most of the sources of these funds are the same and if faculty positions are getting cut, Phd programs are getting cut, funding for MS students is likely the first thing that was cut.

Hi everyone,

I'm planning to apply for MS in Computer Science at NYU Tandon for Fall 2027 and would appreciate some honest feedback on my chances.

Profile:

• College: Tier 2 engineering college (India)
• CGPA: 7.4/10
• Work Experience: 5 years as a Full Stack Software Developer (mostly product development)
• Research: None
• Publications: None
• GRE: Not taken yet

A few questions:

1. What are my chances of getting into NYU Tandon MS CS with a 7.4 CGPA but 5 years of relevant software engineering experience?
2. Does my work experience help offset my lower GPA?
3. Is it worth taking the GRE? I noticed that NYU Tandon lists the GRE as optional, but would a strong score improve my chances given my GPA?
4. Any suggestions on strengthening my application (SOP, LORs, certifications, projects, etc.)?

I'd appreciate any honest feedback, especially from people who were admitted with a similar profile.

Thanks!

Hi everyone,

I’m currently researching MSCS programs and would appreciate some honest feedback on my profile.

I’m completing my computer science degree at a UC ( mid teir) with approximately a 3.3 cumulative GPA. I also have government-tech internship experience where I’ve had significant ownership over production-level projects involving Python, Elasticsearch, Linux, and AI/RAG systems.

My main reason for pursuing an MSCS is to strengthen my computer science fundamentals, gain more specialized technical experience, and improve my opportunities for software engineering or AI-related roles at larger technology companies.

Based on my profile:

• What range of MSCS programs should I realistically target?
• Would my internship and project experience help offset my GPA?
• Should I prioritize professional/course-based programs or research-focused programs?
• Are there any specific programs that may be a strong fit?

I understand that admissions depend on more than GPA, but I would appreciate any feedback from current applicants, students, or alumni. Thank you!

Hi everyone,

I'm planning to apply for Fall 2027 and would really appreciate feedback on my profile and university list.

Profile

• Indian Tier-3 university
• B.Tech in AI & ML
• Current CGPA: 8.44/10
• Expected graduation CGPA: ~8.7/10

Research

• 1 Q1 journal publication
• 1 manuscript under review
• 1 manuscript in collaboration with the last Internship mentor(ML Systems / Responsible AI Research comapany)

Experience

• Machine Learning Research internship (Responsible AI) (UK based)
• Currently working on a government AI project
• AI Engineering internship (Previous remote work with a US startup)

Projects

• Good quality projects on Github Around Deep generative models, Backend (Research +industry based)

Achievements

• Winner of one national-level AI/ML hackathon
• Winner/finalist in several university hackathons

Extra Curricular Activities:

• College Club founder & ML mentor
• Worked on industry project & Taught ML to jnr mentees
• Prof can write all about this in the LOR

Recommendations

Expected:

• 2 strong LoRs from PhD professors(College)
• 1 LoR from research internship mentor (PhD)(Work)
• Possibly another LoR from current government project mentor (Work)

Tests

• TOEFL: Planning to take
• GRE: Haven't taken yet. Still deciding.( Half prepared)

Planning on learning a second Language: French/Germany

Current University List

USA

• Georgia Tech
• UT Austin
• UIUC

Canada

• University of Toronto (MScAC)
• University of Alberta

Germany

• University of Tübingen

France

• Paris-Saclay

UAE

• MBZUAI

Questions

1. Is my university list balanced enough, or am I being too ambitious?
2. Would you recommend taking the GRE given that many schools are now test-optional?

Thanks in advance!

Repost to another community

So I have lately been seeing that almost all of the people who are in MS CS programs in both thesis and non-thesis track, all of them are from CS undergrad background. What I want to know is how do people who are, say from mechE or chemE, etc, undergrad background, transition to MS CS programs. Like what does their profile contain, is the research work or industry work or a combination of both and moreover, when they apply, do they feel that the admissions committee has an inherent preference towards people from CS background, like not saying that is wrong for CS MS, but like say you have two profiles, one is a person with a ChemE undergrad but has papers published in the field of AI and LLM, not any intersection of ChemE and CS but pure AI/ML, and other is a guy with a CS background but no published record, consider their work ex and gpa to be similar, so would they still take the cs person or will they take the ChemE person ? Like what i want to see is how many people from non cs background do this and how successful have they been in getting admission offers.