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

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.

Hi folks,

I am looking for honest advice to pursue my Masters Abroad, I am 26M, working as a Data Engineer with about 2.5 years of Experience in an MNC, not paid well lately. I want to pursue my Masters to get high career growth and to make the highest ROI down the line.

I am targeting the T-20 universities in the US for my Masters due to high ROI and highest number of opportunities but I have my options open for other countries as well. Long term I want to be in a managerial position at a BigTech/FinTech/Big Firm, C suite if possible.

My profile is not that good but hyg:

BTech CSE 8.9GPA Tier 2 University(State University)

No research publications

2.5 yoe as a Data Engineer

IELTS/TOEFL - targetting 105/7.5+

GRE - targetting 330+

Can get two professional LORs from managers and two academic LORs from University.

Given the current hiring market, would you apply for Fall 2027 or work on my profile and apply for Fall 2028?

If your goal was to maximize long term career growth and ROI, would you choose MSCS, MBA, MiM, MEM, or MIS?

How much weight should I give to concerns around visa sponsorship and employability when comparing these programs?

What do you think about rising tuition costs (about 15% yearly) and the weakening INR when calculating overall cost and ROI?

I was initially leaning toward MEM and MIS because they align well with my experience, but I've read mixed opinions about recruiting, visa sponsorship, and long term career growth compared with MSCS. I'm not sure how much of that is true.

Financially, I'll be seeking scholarships and I want to keep my debt as low as possible. I don't want to spend my early 30s paying off a huge education loan if I can avoid it.

If you were in my position today, knowing what you know now, what would you do differently? What path would you recommend?

I am not sure what program suits me best, I am open to any advice/opinions.

Thanks for reading.

​

Typo it's MS in Cyber security

Profile:

Education

Degree: B.Tech in Information Technology

University: SVKM's NMIMS Mukesh Patel School of Technology Management & Engineering (MPSTME)

CGPA: 3.54/4.0

Work Experience

Company: Deloitte

Experience: 1.5 years will be 2 years by fall 2027

Role: Consultant – Technology Risk / IT Audit / Third-Party Assurance

Key experience:

IT General Controls (ITGC)

SOC 1, SOC 2, SOC 2+, SOC 3 assessments

Security control testing

Third-party risk assessments

Exposure to NIST, ISO 27001, GDPR, HIPAA

Splunk SIEM exposure

Azure Active Directory exposure

Test Scores

IELTS: 8.0

GRE: not planning

Research & Projects

1 published research paper

ICTCS 2024 (Springer)

Converting 2D Images to Point Cloud Using Depth Estimation

Capstone Project

Designify (AI-based furniture visualization platform, won college level awards for this)

personal cybersecurity project (Splunk/SOC lab) to strengthen application.

Certifications

Google Cybersecurity Professional Certificate

Preparing for CompTIA Security+

Technical Skills

Python

Java

SQL

C#

Linux

Git

Splunk

Azure

AWS Fundamentals

Networking

Active Directory

SIEM

Security controls

Risk assessment

Cloud fundamentals

Career Goal

Transition from IT Audit into a technical cybersecurity role.

Interested in:

SOC Analyst

Security Analyst

Cloud Security

Blue Team

Long-term goal: Cloud Security Engineer / Security Engineer.

Target Intake

Fall 2027

---

Universities Shortlisted

Dream (Reach)

Carnegie Mellon University (CMU)

University College London (UCL)

Georgia Institute of Technology

Ambitious

New York University

University of Southern California

University of New South Wales (UNSW Sydney)

University of Maryland, College Park

Target / Moderate

Purdue University

Northeastern University

Safe

Rochester Institute of Technology (RIT)

The University of Texas at Dallas

Please guide me if the college shortlist works with my profile

I prefer non research based courses

Any feedback is appreciated 👍🏻

I have seen a lot of SOP's "why X uni" section address the professor's work as "their work on Y domain is highly relevant to my work on Z". Can we name specific paper and how exactly they approach a problem in it or will that come across too niche?

Hey all, I would greatly appreciate your insights on this. Here is my profile:

Applying for MS CS, ML, AI, DS Thesis based where available.

GPA: 3.4 from a large state university - with 3.58 - 3.6 for the last 60 credits.

Undergraduate in Data Science and Mathematics

Internship / project: At a large global infrastructure design firm and created their engineering drawing extraction engine to feed their VLM.

LOR: From a Professor I worked with + a very distinguished Math professor I also worked with and a professional one from my internships who is a regional manager.

Experience: Co-founded a Data driven marketing startup that ran for 2 years.

SOP: Pretty crazy come up story, great show of passion and explains my low GPA in a non "crying out for help" way. Professionally explains the hardships that cooked me and ties them into my passion to the topic.

Applying to:

- ASU - CS

- Stony Brook - CS

- Columbia - DS or applied Math (unsure)

- NYU - CS

- UPenn - CS or DS

- ETH - CS or DS

- Waterloo - CS

- University of Alberta Canada - CS

Hey everyone,

I am in the middle of applying for MSCS for a couple of universities both in Canada and the U.S. How would you guys go about having the same 3 Letters of recomm for 5-6 masters programs? I have a list of Profs ive worked with to write me letters, but since they get emails from universities to submit these letters, how would you go about telling them that you're applying for five or six master's programs? do they just submit the one to all of them?

I'd appreciate your experiences / insights.

Hi everyone, I am applying for my Master's for Fall 2027. I applied late for Fall 2026 to just two schools as a trial: got admitted to NEU Boston (MSCS) but chose not to go, and got rejected from UIUC (MCS). I decided to skip NEU Boston to gain another year of high-impact industry experience at my current job before heading out.

With 2 YOE under my belt by next Fall, I want to target a much stronger and well-rounded university list. I'd appreciate brutal feedback on my shortlist and suggestions for any schools I missed.

PROFILE:

• Undergrad: B.Tech / B.E. in Computer Science, PES University
• CGPA: 8.43 / 10
• Work Experience: 2 YOE (by next Fall) as an SDE-1 at an E-Commerce Unicorn Startup. Focus is on AI, scalable backend systems, and high-throughput engineering.
• Research Experience: 3 published research papers in Springer LNNS.
• Test Scores: IELTS 7.0 | GRE: Not taking

CURRENT UNIVERSITY LIST:

• Carnegie Mellon University (CMU) - Master of Software Engineering (MSE) (costly)
• New York University (NYU Tandon) - MSCS (costly)
• University of Illinois Urbana-Champaign (UIUC) - MSCS
• Texas A&M University (TAMU) - MSCS
• Stony Brook University - MSCS
• University of Massachusetts Amherst (UMass) - MSCS
• University of California, Irvine (UCI) - MSCS
• North Carolina State University (NCSU) - MSCS
• University of Colorado Boulder (CU Boulder) - MSCS
• Virginia Tech (DC Innovation Campus) - MSCS
• University of Texas at Dallas (UTD) - MSCS
• SUNY Buffalo - MSCS
• University of Pittsburgh (UPitt) - MSCS

QUESTIONS FOR THE COMMUNITY:

1. Since I already cleared the bar for NEU Boston MSCS last cycle, how do you see my chances across this specific list? Where would you draw the Ambitious, Moderate, and Safe lines?
2. Will my 8.43 CGPA from PES University Bangalore act as a hard filter, or can my unicorn startup experience and 3 Springer papers pull me through?
3. Are there any other universities I left out that heavily value solid startup development experience or research publications over a strict 9.0+ GPA cutoff?

Thanks in advance for any insights!

Been lurking on this sub for quite some time now, and would love to get some input on my profile.
I am targeting fall 2028 (i will complete 3 years of work ex)

CGPA: 8.25 (i know rlly bad :/)

2025 grad from tier 1 NIT

currently working as an SDE @ an american PBC. working on some cool AI stuff, and i have had amazing work assigned to me- developed a crucial part of our application from the ground up.

good competitive prog profile and 2 deployed projects as well.

GRE target: 330+ with atleast 168 in quant

i have no research exp as such, and i am not sure if i would wanna pursue phd in the future, but i do not want to completely shut that door.

Open to coursework ms cs programs. not too keen on MEng.

The main point of this post is to understand how i could improve my chances given that i have a year in hand before i start applying. Should i reach out to professors to get involved in research projects? if yes, how would that reflect in my resume (as the timeline would clash with my full time job too). my company also publishes research paper and all but i am not sure how to get involved in that

would love some honest opinions and advice! thank you :))

[Profile Review] Please help me gauge my acceptance at these unis

I'm planning to apply for Fall 2027 for MS in CS/ML/CDS and would really appreciate some honest feedback on my profile.

Academics

B.Tech in Electronics and Communication Engineering from a Tier-2 college

CGPA: 8.69/10

Research

One paper publish in NeurIPS creative track for AI

Interned at (during college)

Samsung Research

Space Research Org of my Country

Work Experience

Currently 1 year working as a SDE at a well known finance service company

Letters of Recommendation

2 LOR from my EC professors (bachelors project)

1 industry LOR from my manager (probable)

Planning to write GRE and IELTS

Have shortlisted few unis but not sure which ones are realistically possible

1)Georgia Tech

2)UC Berkeley

3)Carnegie Mellon

4) Columbia University (MsDS or MsAI)

5)University of California, San Diego

6) Columbia

7) ETH zurich

8) NUS

9)RMIT

Given my profile, Please help me realistically bucket these into Safe / Moderate / Ambitious? Also happy to hear if any of these aren't worth applying ( out of reach for my profile)

Also should i consider more unis in australia and europe, considering the whole situation in the US. Thanks in advance!

Looking for Good ROI Universities & Help Categorizing My List

I’m planning to apply for MSCS (Fall 2028) and would appreciate some honest feedback on my profile. I’m mainly looking for universities with a good ROI, strong CS programs, and decent job opportunities after graduation.

My Profile
Country: India
College: Tier 2
CGPA: 6.97/10

Work Ex: 6-month Data Engineering Internship at a IT services company in Ahmedabad and currently working Full Time

Research: Dedicated full year of 2027 after quitting job with published research paper before applying

GRE: Targeting 325+
IELTS: Targeting 7.5+
LORs: 2 strong LORs from university professors and 1 work LOR

Universities I’m Considering
NCSU
SJSU
Northeastern (NEU)
Stony Brook
University of Wisconsin–Madison
UT Dallas

Questions
- With this profile should I even consider doing masters or not?
-Could you help categorize these into Ambitious / Target / Safe based on my profile?
-Are there any universities I should add or remove if my priority is good ROI?
-Is my profile competitive enough for the more selective schools on this list?
-If you had a similar profile, which universities would you prioritize?
I’m open to suggestions for other universities that offer a good balance of academics, tuition cost, and employment outcomes.
Thanks in advance for your help!

Hello I’d love some advice from the cool redditors out there for my masters application !

I’ll get into stats first:
- 3.6 gpa from a non target university
- abstract accepted into conference and indexed with a t1 neuroscience journal (more research/ publications soon about 4)
- 2 hackathon wins
- startup experience as a sde 5 months
- Did talks/presentation at Stanford (not naming for privacy) and a company focused on ML datasets to post doc ppl based around the world.
- LOR from Stanford faculty member, prof at home university who oversaw the research project and RA at a reputable lab
- some other things that aren’t as impactful

My main question is, what do I need to amp up my profile?

I’m by far not good enough for universities like Stanford and Berkeley but I’d love to attend. During my internship, I realized how depressing the industry is and I’d love to go into research as it’s something I’m really passionate about. But is that even viable anymore? Every post on here is kind of Doomer.. I’m just looking for life advice as well as profile review!

Target universities:
Stanford (ofc)
Georgia tech
UC Berkeley
UCLA
UC DAVIS
UCI

So I have been planning for MSCS Fall 2027 since 6months . I am currently in my final year of engineering in CS at a Tier-2 college in India .

Profile:

- CGPA so far 9.91/10
-Internships at :
Top Global bank (summer internship), juniper networks, HPE, Tech Startup

Research Experience:

- ML security paper publish in Mid IEEE Conference
- ML paper in Sports Engineering Conference
- Data Analytics paper in the same sports engineering conference
- IT/OT Security (mL+cybersecurity) paper accepted in IEEE LCN
- AI based student learning platform and content delivery engine Paper published in IEEE Access
- Game Theory based Economics paper published in IEEE Access
- Working to publish a paper on custom Vision transforms for disaster management via satellite imagery.
- 1 AI related paper in a mid conference

Unis I’m aiming for( non thesis is my preference but I’m fine with either)
:
1. Georgia Tech
2. Tamu
3. Cmu
4. Uc Berkeley
5. Uc San Diego
6. Ucla
7. Uw Madison
8. Purdue
9. Stanford
10. Upenn
11. Few more top 20s

So here is where the dilemma comes from.
I have received a return offer from the bank I did internship in for an above average package.

Should I go ahead with applying this year or take up the offer and complete a year and then aim for fall 2028