I was in the same position in the month of March—seeing my expected rank good enough to get MTech in one of the IITs, but not being sure what I should prepare before going there.
So I thought of creating this blog so that others can get an idea of what they are signing up for.
A little introduction: I completed my MTech from IIT Madras in 2025, so the experience is still quite recent for me.
The overall timeline for MTech in most IITs and NITs is that the first two semesters are mainly for coursework, and the third semester is usually when placements happen—something most of you are probably waiting for.
If you arrive without preparation, the first two semesters can become very hectic. Many of us come from Tier-3 colleges where we are not used to intense academic pressure or relative grading. At IITs/NITs, you will be competing with BTech students, your MTech classmates, and sometimes even MS and PhD students in the same courses. Because of this, maintaining a good CGPA can be quite challenging.
You might often hear people say that “skills matter, CGPA doesn’t.” In my experience, that is not completely true in IITs/NITs. When companies come for campus placements, CGPA is usually the first filtering criterion. Skills are important, but CGPA often acts as the primary screening factor.
So before you arrive on campus, try to utilize the next three months effectively by preparing the following resources. This preparation will help you in coursework, internships, and placements. It will also allow you to add some of these skills to your resume. Later, when you start preparing for placements, you will only need to revise these topics, which saves a lot of time and builds confidence.
- DSA:- This is one of the most important things for placements. Most of the coding questions asked during campus placements are similar to problems from the Striver Sheet or NeetCode Sheet. Completing these will give you a strong advantage Link .
- Linear Algebra:- This is very important for coursework as well as for understanding machine learning concepts. Good lecture series are available from Gilbert Strang (MIT) or Prof. Vittal Rao (IISc), both on YouTube. link or vittal_rao .
- Deep Learning :- I suggest starting with Deep Learning instead of traditional Machine Learning courses because many ML resources are mathematically heavy and difficult to follow initially. A very good and intuitive course is the Deep Learning lecture series by Prof. Mitesh Khapra. His explanations are very clear and also cover important ML concepts with simple diagrams and intuition. You can learn the more theoretical ML parts during your coursework in college. Link .
- Puzzles:- This is often ignored but very useful. Try solving one puzzle every day from common interview puzzle collections. By the time you reach campus, you may finish the top 100 frequently asked puzzles in interviews. Puzzle
A few additional suggestions:
Make as many friends as possible.
Build good relationships with faculty members.
Do not hesitate to ask even the simplest questions in class.
Avoid bragging about your GATE rank.
Join clubs and participate in social activities. These will not negatively affect your studies.
Most importantly Enjoy your college life as much as possible . If anyone need any help or suggestion feel free to ask in telegram.(@Kabir5454).
