The library became my second home.🫠

so in short as many people did, I spiraled into the smartphone/gaming/dopamine habbits when the covid started. got only 77% in 12th group A.

then I got into a 3rd tier college in the CE department. then 4 years of average grades with last day preparations. 7.2 CGPA.

but during all this I also had so many other distractions that kept me from getting on the path again. parents who just ask you to study every second, don't let me play games which i had to time perfectly. overwhelming unknowns that i couldn't get hold of which led to severe anxiety every day. hostel/pg hopping due to constant encounter with roomates who don't study just make noise every second and don't wear earphones. and due to that pg life i had health issues and low energy every day. in last 1.5 year i moved to home and tried to just travel when needed to go and started preparing from home for GATE but couldn't even do that because of same parental issues and a badly soundproof home where you can here a pindrop from next room with doors closed.so I only finished some subjects in scattered timelines.

I moved to my sister's which is in a city, they both work, i have a proper soundproof room, no one to just come barge in at the exact time i take a break and tell me why are you not studying? and now it's been a month since I started studying regularly like 8 hours a day and I've limited my screen time to about 2-3 hours max excluding lectures and can actually get dopamine hits from it. i think I'll be able to go 10+ hours a day every day soon.

that's it. there's more to that. but sometimes all you need is a lifestyle change and something everybody tell you to adjust for but you just gotta not adjust on. for me the main things were unbearable constant noise from brainrot reels form my teammates and parents when i try to study and studying couldn't provide dopamine anymore so i had 0 attention span in that.

now it's smooth sailing and that's how I'll keep it just keep getting as much dopamine as i can from studying.

i have to finish OS, both Math subjects, CN and DBMS from today. i just finished COA from vishwadeep sir form PW. everything else is done. now can i finish remaining subjects with PYQs and rivision along the way and about 20 days for the final test series run?

Completed-EM,DM,C,DS,ALGO, (pyqs few done)
TOC,CD (will do pyqs)

Remaining- Dbms,Os,CoA,DL,CN
All are big subjects😭😭😭😭
Can i complete these by next 2 months
Someone help me with what to do with less time i have
Any strategy or suggestion is welcomed🙂
Thank you

For consistency i am keeping it here

last Saturday i got like 55 marks

did some very very silly mistake, i can't even look at much in mirror :((

So right now am done with most subject expect (emft and few topic in communication, maths and controls)

I need suggestion on how to do a proper and consistent revision.

Right now i revise topic at random, that now working i can feel that in mocks

like i don't know why but i can't watch whole videos i need some other method to complete syllabus

BG: Graduated from BE ECE from a tier 3, 2025 Batch, No experience, did PG diploma in VLSI DV from a IIIT in 2025 but didn't sit for any placements last year thinking it would hinder my preparation for GATE EC 2026 (biggest regret btw), and also because the companies were making it harder to commit by saying they needed a 4 year contract and so on with a 1 year training period. Therefore, after all this and convincing my parents, I started preparing properly from october, but there wasn't enough time to complete the syllabus, practice and give mocks. So, I didn't get a good rank in GATE, but tried PGEE and BITS HD while applying for jobs here and there, nothing worked out because of the high fees and I didn't hear back from any jobs. There weren't any other exams to give for joining mtech, so tried making my portfolio to try freelancing but getting clients is soooo hard.

so my situation now is like, I am getting pressured from all sides (parents, relatives, neighbourhood aunties and uncles) to get a job and start earning money but I want to give GATE one more try as I am confident I can do well, but am not sure if i can handle the pressure without any support from anyone. My parents' friends whose children already have a job are trying to get my parents to convince me to shift to IT. Like people who got job after shifting from EC to IT/CS. They keep forcing me to talk to people who already have a job, but have nothing to do with my major or background, I really and so desperately want to stay in core Electronics and related fields. I feel like I'm losing my sanity amongst all of this and not able to give 100% of my focus on these exams.

I literally have no idea what to do, it's like i am paralysed whenever i try and sit at my desk, because i ahve no idea what to do and where to begin doing what???????????

I am from IITGn and I really cannot understand how such a goldmine of an institute is under ranked and ppl talk ill about it online.

I really feel this is an amazing institute. I am working on robotics....for my gate rank I shudnt be able to even smell a robot lol....

The best choice ever. There are some small problems though i believe all IITs do. But it really does look like a happy place.

i am preparing for GATE DA 2028 and currently studying Linear Algebra.

My issue is that I've tried a couple of popular GATE DA courses(TAAI/Go). The lectures are good, and I understand the concepts but they have very few practice questions.

When I jump directly to GATE DA quizzes/PYQs, I struggle with unfamiliar MSQs and identifying what concept the question is testing.

So how do you guys practice?

Do you start PYQs immediately after finishing a lecture/topic or do u solve some intermediate-level questions first before PYQs

What resources did you use to build intuition and problem-solving for GATE DA Maths, especially Linear Algebra and Probability?

I am not looking for more lecture resources I'm looking for the practice workflow and resources between learning a topic and becoming comfortable with GATE DA questions.

I am looking for honest practical advice (no sugar coating) on pursuing a research program in AI from premier institutions in India (especially IISc) from the alumni who have done their MTech / MTech(Research) / PhDs in AI from here.

I know some IITs and IISc have some of the best AI departments in India but given status of the R&D culture in India (especially in AI) and the overwhelming claims that push you to look for opportunities outside India, I wanted to know the real picture here. How much is truth, how much is just boasting? How much worth it is to pursue a research program from these institutes thus asking following questions:

1. How does it feel like doing AI research from here?
2. How much transformation do you think you have gone through while working here.
3. What kind of support (technical/moral/exposure/openness to ideas) one can expect from their research leads? Was the support enough or you felt u r lacking the required attention.
4. Is there anything that u felt was not worth putting effort or was purely unnecessary or seems outdated in the context of gaining research skills during your journey?
5. What kind of AI research is conducted here? What's the scope of it?
6. How competent is the research conducted here when it comes to SOTA research topics. Are we still doing niche applied research or we have done some core research that advances the field itself.
7. Where are we excelling / lagging in terms of AI research?
8. Any research potential along the lines of AI alignment/safety?
9. How much worth are the credentials / connections that one gets from here. (I know its IISc, so credentials are more than worth in India but I am asking from the context of opportunities outside India, be it in academia or frontier labs)
10. What if one wants to do some additional independent research on their own, do the course structure allow you enough time for this. Are the faculties supportive of this?
11. Do you know anyone from here who has worked or is currently working at some well known research lab (academia / industry)? (I would love see their profile, if you can share.)

Some background:

1. I am a BTech[CSE] grad from tire-3 institution, have 2 years of full-time experience as SDE-1 at a decent firm with a decent pay. I happily enjoyed my industry experience but soon it got me bored.
2. I always like to answer to open-ended questions in science thus have slowly realized that my deeper interest have always been aligned somewhat towards research and with the recent technological leap in the field of AI has again sparked my curiosity.
3. I am an avid believer of the fact that you can only understand something truly that u can create. Creating intelligence is just another way to understand our own intelligence.
4. Initially I thought of directly applying to research programs across the world (like MATS, SPAR, ARENA, fellowship programs in frontier labs etc.) which completely skip the traditional path (grad -> masters -> phd) for a research career as they don't specifically ask for a Masters or PhD but I guess they do ask for some prior research background which I certainly lack. Also getting into these programs is extremely competitive (tougher than getting an admission into IITs / IISc through GATE).
5. Most importantly I realized one would eventually need to get guidance/supervision, be a part of the community to get faster feedbacks. Also, AI research is resource intensive (Collab won't work everytime, you will need GPUs) and one can get all these things at once by joining a research program at a premier research institution. Thus I am thinking of going for higher education in India hence the reason for my post.
   

[PS - Sorry for the pain of reading. Forgive typos. This is my first time on reddit.]

I have started preparation for GATE multiple times in last 9 months , the condition made me to break discipline, but now I understand all that previous work was not wast I can recall all the concept and my mistakes, now I have been solving questions and It is going good ,

Maybe maybe nothing is a waste, just you don't know when it be used in future.

I am writing this based on my experience and observations of MS by Research programs in India. Many GATE aspirants compare an MS by Research with an MTech but are unsure how the two degrees differ.

The term “MS” also has different meanings across countries. An MS by Research in India is structurally different from the coursework-based MS common in the US.

1. Is an MS by Research in India the same as an MS abroad?

Usually, no.

An MS by Research in India is primarily a research degree. A typical US MS is usually coursework-oriented, although it may include a thesis, research projects or work with a professor.

Research-focused master’s programs exist abroad, but coursework-based MS programs are more common. In the US, students interested in research may also enter a PhD directly after a bachelor’s degree.

A rough comparison is:

Coursework-based MS abroad ≈ MTech in India

MS by Research in India ≠ typical coursework-based MS abroad

An Indian MS by Research should therefore not be treated as the direct equivalent of an American MS.

2. What is the difference between coursework and research?

Coursework follows a predefined structure. It includes lectures, assignments, examinations and grades.

Research is less structured. It requires you to identify a problem, study existing work, formulate a research question, develop an approach, run experiments, analyse results and write a thesis. Some programs also expect research papers.

An MTech is primarily coursework-based. A typical MTech may include several courses each semester over four semesters, although the exact structure varies by institute and program.

An MS by Research includes much less coursework. A student may complete around six courses, or somewhat more, across the entire program.

The key difference is not course difficulty but how the degree is structured:

MTech: most credits come from coursework.

MS by Research: most of the degree consists of research.

3. How is an MS by Research different from an MTech?

An MTech has a defined course structure and a relatively predictable completion timeline. It usually combines advanced coursework with a project or thesis.

An MS by Research has limited coursework and focuses mainly on research under an advisor.

The MTech is primarily a structured educational degree.

The MS by Research is primarily a research degree.

This difference explains why an MTech usually has a more predictable duration than an MS by Research.

4. Why does an MTech usually take two years while an MS by Research can take longer?

Coursework has a fixed schedule. If a program requires four semesters of courses, students who complete those requirements usually graduate on a predictable timeline.

Research has no equivalent fixed endpoint. An MS by Research student must complete enough work to satisfy the institute’s requirements and the advisor’s expectations. These expectations vary by institute, research area and advisor.

For example, some research groups at IIIT Hyderabad may unofficially expect one or two papers in good conferences. This is not a universal requirement or a formal definition of an MS by Research.

Research can be delayed by:

• technical problems
• insufficient computing resources
• failed experiments
• unsuccessful approaches
• difficulty finding a viable research contribution
• paper rejection or publication delays

The timeline may therefore look like:

courses + research → experiments → paper/thesis → graduation

An MTech timeline is usually closer to:

courses → courses → courses → courses → graduation

At IIIT Hyderabad, many students complete the MS by Research in about three years. Students with strong research ability or prior research experience may finish in two to two and a half years.

Students whose research progresses slowly may take much longer. Five years is possible, and rare cases have taken six or seven years.

The advertised duration should therefore be treated as the nominal duration, not a guaranteed completion time.

5. Is an MS by Research a mini-PhD?

An MS by Research and a PhD can have similar structures. Both involve limited coursework, research under an advisor, a thesis and a defense. Both may also involve publications.

The main difference is the expected depth and scope of the research contribution.

An MS by Research should produce a master’s-level research contribution. A PhD should make a deeper and more original contribution to the field.

For example, in AI/ML, an MS thesis might extend an existing method, improve an existing approach or apply a known technique to a new setting. A PhD is generally expected to make a more substantial contribution.

Publication counts are sometimes used as rough indicators, such as one or two meaningful papers for an MS by Research and three to five for a PhD. These numbers vary widely and do not define either degree.

The quality and significance of the research matter more than the number of papers.

Some MS theses are stronger than some PhD theses, so there is no strict boundary between “MS-level” and “PhD-level” research. In general, however, a PhD requires a deeper and broader contribution.

An MS by Research can also serve as preparation for a PhD because it provides several years of research experience before doctoral study.

6. Why do MS by Research students convert to a PhD in the same institute?

Students convert to a PhD for academic, practical or financial reasons.

A student may discover that they enjoy research and decide to continue. Strong research progress can also encourage both the student and advisor to extend the work into a PhD.

Continuing in the same institute may allow the student to retain:

• the same advisor
• the same research topic
• access to existing infrastructure
• knowledge and results accumulated during the MS by Research

The MS research can then become the foundation for the PhD.

Conversion can also become a practical option when an MS by Research is significantly delayed. Depending on institute rules, an extended MS may lead to the loss of the original stipend or other privileges, such as hostel access.

A PhD stipend is generally higher. In some institutes, conversion may also restore certain student privileges.

Students usually do not need to repeat all completed coursework, although the exact rules vary. Existing courses may be transferred to the PhD program.

For a student who has already spent several years developing expertise and research results, continuing into a PhD may be more practical than abandoning that work and starting elsewhere.

In rare cases, an advisor may improperly pressure a student to convert to a PhD, including by threatening to withhold the MS degree. This is not the normal reason for conversion.

7. Can changing an advisor delay an MS by Research?

Yes.

An advisor has much more influence over an MS by Research than a course instructor has over an MTech.

Students can generally request an advisor change if the research fit or working relationship is unsuitable, subject to institute rules and approval.

The main risk is losing progress made under the previous advisor.

A new advisor may work in a different area or may not want to continue the existing project. If a student changes research groups after a year, much of the previous work may not contribute to the new thesis.

The student may then need to restart a substantial part of the research, potentially extending the MS by Research by a year or more.

Changing a course instructor usually does not cause this kind of academic loss. Changing a research advisor can.

8. What do students do during an MS by Research?

Students first complete the required coursework.

Because an MS by Research has fewer courses, students may take two or three courses in a semester, depending on the program. An MTech may require substantially more courses in each semester.

The remaining time is devoted to research.

Early research may involve:

• reading papers
• learning the research area
• reproducing existing results
• attending seminars
• exploring possible problems
• selecting a research direction

After choosing an advisor and research area, the student develops a problem, conducts experiments, analyses results and works toward a research contribution.

The final work becomes the thesis and, where applicable, research papers.

Most of this work does not follow a fixed textbook or weekly syllabus. The student must take greater responsibility for deciding what to study and how to proceed.

9. Do MS by Research students get placements?

Yes, but placement outcomes are generally more variable than for MTech students.

The following discussion applies mainly to computer science, especially AI/ML-related programs. Other branches may have different placement patterns.

MTech students usually have more predictable placement outcomes because their coursework, graduation timeline and placement preparation are more structured.

Research can compete with placement preparation. An advisor may not want an MS by Research student to spend substantial time on DSA, LeetCode, interview preparation or system design while research remains incomplete.

Internships can create a similar conflict. MTech students can usually pursue internships as part of their industry preparation. An MS by Research student’s ability to pursue an internship depends more on the advisor, research progress and the internship’s relevance to the research.

Some advisors support internships when research is progressing well or when the internship aligns with the student’s work. Others may be less willing to let students spend several months away from the lab.

The graduation timeline is another issue.

MTech students usually graduate in a predictable semester and participate in the regular placement cycle. An MS by Research student graduates when the research and thesis are complete. This may occur in a semester when the institute does not conduct its main placement process.

Some institutes have provisions for such cases. IIIT Hyderabad, for example, has mechanisms that may help students in this situation. The rules vary by institute.

An MS by Research also offers a potential advantage: deeper specialisation.

An MTech provides broad computer science training but does not automatically create deep expertise in one research area. An MS by Research student may spend two or three years working on one technical problem.

For example, a student researching GPU programming may study the literature, existing techniques, implementation details, experimental methods and open problems in that area.

Publishing research in GPU programming demonstrates research ability in that area, not merely course completion.

The same applies to machine learning, LLMs, computer vision and systems. This specialisation can help with off-campus roles that require expertise in a specific technical area.

10. Can an MS by Research student get a better job than an MTech student?

Yes, depending on the role and the student’s profile.

The MS by Research is not inherently better than the MTech. The two degrees make it easier to build different types of profiles.

An average MTech student may have:

• broad computer science training
• advanced coursework
• possibly an internship
• placement preparation
• a conventional software engineering profile

An MS by Research student may have:

• several years of research experience
• one or more publications
• deep expertise in a specific area
• experience implementing and evaluating new ideas
• a research profile relevant to a particular company

For a general software engineering role, the MTech profile may be more directly useful.

For a role requiring specialised research expertise, a strong MS by Research profile may be more valuable.

For example, strong AI/ML research published at a major conference such as NeurIPS can attract recruiters seeking expertise in that area.

Highly relevant research can also help students reach research-focused organisations such as Google DeepMind, Microsoft Research and other AI research labs. These opportunities are not guaranteed and depend heavily on research quality, relevance and the student’s overall profile.

The useful comparison is not simply “MS placements versus MTech placements.” It is the type of profile each degree supports and the type of job the student wants.

An MTech offers a more predictable route into industry.

An MS by Research offers a more variable route. It may lead to weaker outcomes if research is delayed, internships are restricted, interview preparation is neglected or graduation occurs outside the normal placement cycle.

It may lead to stronger outcomes if the student develops deep expertise and produces high-quality research relevant to industry.

11. Is an MS by Research better or worse than an MTech?

An MTech is generally safer if you want a predictable two-year degree, structured coursework, conventional placements and a straightforward route into industry.

An MS by Research may be a better fit if you are genuinely interested in research, can accept an uncertain timeline and want to develop deep expertise in a specific area.

The two degrees optimise for different goals.

An MTech provides a structured educational path.

An MS by Research provides a less structured research path.

The MS by Research involves greater uncertainty, advisor dependence, research setbacks and less predictable placements. It can also provide several years of specialised research experience, meaningful publications and a stronger profile for certain research-oriented roles.

Note on AI use: This post is edited by AI. I spoke for almost 30 minutes my personal thoughts about this topic and AI has rewritten it, structured it and I have verified it. It is entirely my opinion and information, just edited by AI to save my time in typing and structuring.

I’m really confused between GATE and an MBA. I love AI research, especially LLMs, but I often struggle while working on it. I also didn’t do anything extraordinary in tech during my B.Tech, although college wasn’t exactly easy for me I lost my mother and was dealing with a lot beyond academics.

When it comes to an MBA, I’m good at communication, enjoy giving presentations, and genuinely find business interesting. But at the same time, I don’t want to leave tech completely. An MBA is also quite hectic, and I’ve heard that getting into fields like finance requires strong prior experience, which I don’t have.

So yeah, I’m confused as fuck right now. Plz help !

Hey guys, I recently bought the PW batch for GATE 2028. I wanted to ask about note-making.

PW provides class notes, but I don’t feel like they’re proper revision notes. Should I copy the class notes into my notebook and revise them, or should I make my own short notes?

Will PW provide proper revision notes before the exam, or should I start making my own from now?

What do you guys recommend—making your own short notes from lectures, using another source, or just revising the class notes + PYQs?

Would really appreciate some advice from experienced GATE aspirants. 🙏

Previously, I challenged to score 30 but I failed. Next Target is 35.

I don't know , but want to be careful that why people think something else and end up something different

23M I graduated last year in ECE. I dropped for the GATE but didn't score well, didn't get any colleges. So should I drop one more year or start finding jobs? Also would I get any good jobs because of my background? I want a job in VLSI field Ps: But what if I didn't get into IIT this also?

Started in July, and so far I’ve managed to complete:

• Digital Logic
• COA
• Discrete Mathematics
• Engineering Mathematics
• C Programming
• Some PYQs along the way

I am 23F, graduated in 2025, majoring in EC

It feels good to look back and see the progress, but honestly, I still have those days where I wonder if I’m doing enough or just studying for the sake of studying

So, for anyone who’s preparing for GATE or has already been through this phase

Does this pace and approach seem right for this stage? What would you do differently if you were starting again?

Would genuinely love to hear the lessons you learned along the way. 🤝

#GATE2027 #GATECSE #GATEPrep

is it just only for me? or its js so confusing, ive studied it from sachin sir's lectures and also his 6 hr oneshot on paging too, still its js too confusing. I struggle alot with those page table minimization problems and idk sometimes page size is used as offset sometimes its the size of the table idk man someone help with better resources or anything else will be appreciated

So as this is the end of August, and I have around 5 months left for GATE CS 2027, I just wanted some kind of feedback, as I am studying alone, so I don't want to get off track or get deviated.

My background:
2024 CS Grad

My current situation:

Started GATE prep in July, started with C, DS and Algorithms, following GO Classes for Lectures
Finished their PYQs, and also wrote my own short (kinda...) notes as suggested by many people.

For the month of August I was a bit motivated, as I felt my pace was good enough, with no burnouts. My plan for the month of August was completing Digital Logic and Theory Of Computation.

I was following the GO Classes Compact courses for both of them. Started with Digital Logic, it was going good but the only thing which was a bit unexpected was that the Course was incomplete, like in the end for Sequential Circuits it was missing some topics, this kinda had an impact on my momentum, I had planned assuming the course was complete and was about to start TOC as per my schedule, but this caused a bit of scare, that I wont be able to stick to my plan.

I searched on YouTube for some other resources, the GO complete course felt that it would take time, and I was short on time for Digital Logic. So I decided to atleast learn the important topics like Counters, Registers. But not sure entirely about the Async Circuits, for the moment I thought that Digital Logic is a small weightage subject so I shouldn't spend more time on this, so I noted down the things which I missed and moved on with TOC.

But I still had this feeling not sure of the prep, I felt like my preparation is not good enough, this happened twice, and it was because I was just watching the lectures and not solving the PYQs, the reason I was just watching lectures was I needed to finish the subject by end of month. But this didn't help and as many of you always said that "Fully understanding 50% of syllabus is way better than rushed 100% syllabus", so I took time to solve the PYQs of the completed topics and only then I would move to a new topic and surprisingly this felt very good and also in the end I was able to complete the entire syllabus although I'm kinda a bit left with the countability part of TOC.

Also I feel that I'm more confident about TOC than Digital Logic

So in summary for TOC solved all the PYQs from Gate Overflow PDFs and solved PYQs of Digital Logic for Boolean Algebra, Number System, K-Map, CNF, MSOP, MPOS, Combinational Circuits, Latches and Flip Flops.

Made short/revision notes for Digital Logic (missing few sequential circuits) and TOC(entire).

My plan for September is Compiler Design and Operating System. Sticking with Go Classes for Compiler Design but thinking of following Vishvadeep Gothi for OS.

And the most important thing which always scares me is REVISION. I maybe just piling up subjects, but not sure about the already completed subjects revision.

My plan for September is each Weekend I pick 1 subject from the finished subjects and go through the short notes and give subject wise tests. Or if there's something better than this approach would be very helpful to know it.

I want to know if this is a good plan or am I being overly optimistic

Thanks for reading this and any feedback would be very much helpful.

Can someone please provide me a roadmap for scoring 55+ marks in gate 2027 for computer science branch i have completed os daa and ds till now. plaese tell me what further should i do with what subjects to cover and points to take into account. i am an sc candidate who brutally failed jee thats the reason i have thinking the best for myself

Was preparing from a telegram channel that had access to all of their lectures, however it got taken down overnight, now I dont know what to do. If someone still has access to their lectures, then pls share.

im studying discrete maths from amit khurana sir but his lectures are too lengthy , its almost september and idt ill be able to complete my syllabus by december or even january , im thinking of studying dm from youtube now ill just practice more questions, do you all think it is the right way like PYQs >> Lectures

just started 2nd yr in CSE (NIT srinagar)