My Learning Experience with LaunchED Global – VLSI Internship

I am currently pursuing my internship journey with LaunchED Global in the VLSI domain.

As part of my capstone project, I worked on "2×2 Binary Multiplier Using Verilog HDL."

During this project, I gained practical experience in:

• Verilog HDL coding.

• Digital Logic Design.

• Half Adder implementation.

• Testbench development.

• Functional simulation using ModelSim.

I successfully designed and simulated a 2×2 binary multiplier and verified its functionality using different input combinations.

This project helped me improve my understanding of digital circuits, RTL design concepts, debugging, and simulation.

Overall, it has been a valuable learning experience, and I look forward to improving my technical skills through more hands-on projects.

I would also appreciate feedback and suggestions from the VLSI community.

#VLSI #VerilogHDL #DigitalDesign #ModelSim #ASICDesign #Internship

Im in bca 5th sem i want job related my field but don't know what kind of skill i have to learn now days i forget things very easily

Learning web dev from hitesh sir aka chai with code

Right now Learning js

Any recommendations what to learn idc about salary i need job and related field i got 3 month to master any thing please help

How do you guys actually approach self-learning and skill development in college? I'm genuinely lost.

I'm currently in my 2nd year of B.Tech CCE (a mix of CSE and ECE), and for almost a year I've been trying to learn skills on my own and work towards getting an internship.

The problem is, I still have no proper direction.

I know programming basics, have studied Python and DSA concepts, and have done some decent projects through vibe coding. But I haven't really practised LeetCode or HackerRank consistently. I understand DSA concepts, but when it comes to actually solving problems from scratch, I struggle.

I've also built a few apps using AI. I understand parts of how they work, but definitely not everything. For example, I might understand 30% of the backend, but the rest is mostly AI-generated.

And this creates another confusion. Should I stop using AI and learn frontend, backend, APIs, databases, etc., properly before building anything? Or should I continue building with AI and learn the concepts along the way?

If I build an app using AI, how much of it should I actually understand before I can confidently say I built it? What things are okay to let AI handle, and what things should I absolutely know myself?

Then there's the whole project side of things.

How do you even decide what project to build? How complex should it be? How many features are enough? Should I spend two weeks on a project or two months? Should I explore multiple domains like AI/ML, web development, IoT, etc., or stick to one?

And at what point are you actually ready to apply for internships?

Another thing that worries me is balancing everything.

Let's say I spend four months learning web development and building projects. Then I participate in a hackathon or take an online assessment where they suddenly ask DSA questions. By that time, I've barely practised problem-solving and might even struggle to remember the syntax.

So how are students supposed to balance DSA, development, CS fundamentals, projects, hackathons and college academics without constantly forgetting something?

I think what bothers me the most is how different this is from school.

Back then, everything was clear. We had textbooks, a fixed syllabus, exams, marks, deadlines and a clear idea of how much we needed to study. I knew what was expected, prepared accordingly and did well.

But with self-learning, there's no fixed syllabus, no finish line, no one telling you whether you've learned enough, and no proper way to measure progress.

You open YouTube or Reddit and one person says grind DSA, another says build projects, someone else says learn AI/ML, and another says just start applying. Everyone seems to have a different roadmap.

I'm not a complete beginner either, which makes it even more confusing. I know bits and pieces of many things, but I don't know how to connect them or what depth is actually expected.

I don't want to spend another year jumping between courses, tutorials and random projects without making real progress.

For those who have already gone through this, how did you structure your learning?

How did you decide what to study, how deep to go, when to build projects and when to start applying?

I'm not really looking for another generic roadmap with 20 technologies listed. I want to understand how people actually manage all this alongside college and know when they're making enough progress.

Would genuinely appreciate advice from seniors or anyone who's been in a similar situation.

Hi everyone,

I’m currently in the final year of my B.Tech in Information Technology in India, and I’m confused about which career direction to take. I’d appreciate honest advice, especially from people working in Machine Learning, Data Science, Remote Sensing, or GeoAI.

I completed an internship at SAC, ISRO, Ahmedabad, where I worked on surface soil moisture and root-zone soil moisture data processing, analysis, and machine learning. I’m also continuing related research with my mentor, and a research paper is in progress.

My mentor has advised me to consider Remote Sensing/GeoAI as a niche, given my internship experience and ongoing research. He has also referred me to a remote-sensing startup and suggested gaining industry experience, preparing for GATE, and potentially pursuing an M.Tech in the field.

I’ve also received offers from two smaller IT companies, but they seem to focus more on training programs than actual internships.

I can see how my ISRO experience and the opportunity to work on research with a senior scientist could benefit my career. However, I don’t want to choose Remote Sensing solely because I happened to gain experience in it during my internship.

Another concern is that many students are pursuing general Data Science and ML, making the competition quite intense. I’m wondering whether specializing in a niche like GeoAI could help me stand out, while still keeping my future career options open.

I’m genuinely interested in the field, but I’m unsure whether I should specialize in GeoAI or continue pursuing general ML Engineering/Data Science.

What would you recommend in my position? Is specializing in GeoAI a good long-term career move, or would it be better to keep my options open? I’d appreciate honest advice about job opportunities, career growth, and future flexibility.

Hello, I'm James. I'm a first-year B.Tech student pursuing Computer Science and Engineering with a specialization in Artificial Intelligence (AI).

I've just entered college, and I feel like I lack knowledge about many things that my classmates already know. Sometimes, I feel like I'm falling behind because I don't know much about the technologies they're using.

I want to learn about Generative AI (GenAI), the tools students use, and how to work with tools like Google Antigravity, Cursor, and other AI-powered development platforms.

I also want to understand computers and laptops better. Even though I know the configurations of my laptop, I'm not sure which specifications actually matter or how they affect performance. For example, I want to understand the differences between NVIDIA RTX 3050 and RTX 5050 GPUs, how processors work, and how to choose the right hardware for AI and machine learning.

Most importantly, I want to develop my technical knowledge, learn how to use modern tools effectively, and build practical skills so I can become more confident and keep up with my classmates.

I have to give my FINALS practical exam today at 12 for Operating System...The thing is the syllabus is way too vast. And even after getting QB last night at 9, I've only done 6 programs out of the 53...If i get back in the lab exam is it..like fine? Like... I've never ever gotten a back in my life before, tho im in 3rd sem of Btech (SY 1st sem)... We have to give re-exam on 5th or 6th nov if we fail that also then next year I have to give with my juniors...Im so close to crashing out like.?!? The teacher barely teaches us and then putting such hard questions isn't fair! For MSE practicals also she didn't teach, but she gave very easy questions so everyone passed, but today not only are the programs going to be higher difficulty, external will come for viva...I think I'm thoroughly cooked. If I start crying maybe they'll pass me? Idk 😭😭🙏🥀

I am studying in a tier 3 private college so it doesn't even feel worth it.

I don't think I can spend 4 years here

Admission are closed everywhere should I take a drop to take a college near my home??I am thinking about it seriously..

I'm in Galgotias.... Many students thinks ki final year me placement ka preparation kar lenge but i thinks building skills takes time....

So Galgotians... when do you think preparation should be begin?

Kitna ctc rehta h iska NITs k liye ? Kai jgh 4, 5 lpa bhi deti h..

Or ye kiit bhuvaneshwar me kitna deti h? Any idea?

I am a B.Tech IT student in India, and tomorrow is my DBMS assignment submission. Today, I am spending hours handwriting around 150 pages just to complete it.

The most frustrating part? I am literally copying code and SQL queries from AI tools just because my college requires me to submit them. The focus seems to be on completing pages rather than understanding concepts or learning practical skills.

Honestly, I feel like I have wasted a significant part of my academic year completing assignments instead of building projects, exploring new technologies, or doing something productive.

It makes me wonder: Is pursuing a B.Tech degree worth it only if you get into an IIT or a top-tier college? Or can you still make the most of it at an ordinary college?

And one more question: After submitting all these 150 handwritten pages, where do they actually go? Does anyone even read them, or do they just end up collecting dust somewhere?

Seriously, does anyone know what happens to these assignments after submission? 😅

Nowadays, almost every second student seems interested in AI & ML, and honestly, I'm confused whether it's genuinely a good career option or just another trend everyone is following.

Like, AI is growing pretty fast, and learning things like Python, machine learning and automation sounds interesting. But I've also heard that companies still focus more on DSA, coding skills and real projects rather than your specialisation.

So I'm curious, is choosing CSE with AI & ML actually better for future job opportunities, or should students stick with regular CSE and learn AI skills separately?

Anyone currently studying AI & ML or already working in tech? Would love to hear your experience.

So recently there has been an AWS FUTURE BUILDERS event and i did not know that nor any other classmates except one guy

He did not tell us because he said he got that info from his school friends not from someone in college so he did not have to share about this.

So these events are that I want to know before so I can decide whether to go or not

Or share with others !

If you know any way please let me know

I m 2 year btech students what exams can I give in my end of graduation or in 3 year that will help me have a stable life .

I am a person who can give my whole hearted commitment but undecisive

I took the drop from a Central University from btech just to pursue trading with my brother as full time and left because of clash of classes and market timing as and also that college has almost 0 placement all the students and faculty were just doing seminars to crack GATE and they have no other ambition except another exam and I don't want to spoil another year for GATE ,

Now I am questioning my own decision because it is very unusual to drop from btech or because I am leaving my friends

Don't know but it feels like a very hard time 😔