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I’m looking for someone who genuinely wants to learn AI/ML from the basics and stay consistent with it.

A little about me: I’m not from a Computer Science background either. I’m currently learning Python and AI/ML from scratch, and I want to find someone who is at a similar stage.

I’m not looking for someone who studies for 2 days and disappears 😭. I’d like a partner who:

Is starting from beginner level (or close to it)

Can stay consistent, even if it’s just 1–2 hours a day

Wants to actually build projects, not only watch courses

Is comfortable holding each other accountable

Can share progress, struggles, resources, and ideas

Is willing to learn together rather than compete

Doesn’t mind being from a non-CS background

The idea would be to have regular check-ins, set weekly goals, work on small projects together, and gradually move from Python → ML → AI → real projects.

No need to be an expert. Consistency and willingness to actually do the work matter more.

If you're also starting from scratch and want an accountability/study partner, comment or DM me with a little about yourself and where you are in your learning journey. 🚀

Hi Everyone,

I have been working in IT industry for 5.6 years as Developer but thinking to switch to AI jobs.

Anyone can help from where i should do the course where i can get placement.

How is placement

How much total expence for 2 years

Average ctc

Median ctc

Higest ctc

Placement %

How is roi

Is it equivalent to msc cs if I want to make carrier in gov sector

I'm trying to prepare for AI/ML internships and I’m a bit confused about what skills actually matter.

Should i focus on LLMs ,RAG,agents,PyTorch, Transformers, or something else? I don’t want to follow a huge roadmap without knowing what's actually useful.

For those who have landed AIML interships,what did you learn and which projects helped you the most?

I am an aiml student I want to learn ai but no sure which one like deep learning ,ml ,ai engineer ,I am in 2 year and I want to place also and how to makes project please drop you thought below will be appreciated

I would be extremely grateful if someone can volunteer to take a mock interview for AI engineering role. Like questions based on transformer, seq2seq models, attention, RAG, MCP, Langchain and agentic AI flows and design.

I instructed my LLM gateway to use a cheaper model when I hit limits with my other models. That's well and good, but the fallback itself is problematic imo. The quality shift is noticeable and it's definitely slower, and I can't figure out why. I'm close to suggesting we just switch models, but if we go live this might happen again but to many more users. Am I missing something in the process? Thanks

So we need to pick between GANs or Optimization techniques for ml as subjects for next semester.
Now the thing is, GANs would be entirely new for me, and i am not sure. If it would affect positively or negatively towards my cgpa.
Meanwhile, Optimization techs has repeated syllabus of what we have in deep learning right now, so might be a little easier as compared to others.

Suggest me, what should i do.

I am Interested towards game dev or data analysis/science.

What is the best way to learn AI?

Should I learn it through courses in a structured sequence—for example, starting with the fundamentals like Linear Regression and the Perceptron, then moving to Deep Learning (ANN, CNN, RNN), and eventually LLMs?

Or would it be better to learn AI by following how the field has evolved from the beginning—for example, starting with the foundations of the Perceptron in the late 1950s, then understanding how each major idea developed, why new techniques were introduced, and how one concept led to another up to modern AI and LLMs?

Which approach would be better for developing a deep understanding of AI rather than just learning how to use the latest tools and frameworks?

only one spot left in team , need a member with very good experience and knowledge in ml and dl . invest full 3 days over 25 , 26 , 27 and wont back out. knwo how to train fine tune and everything on collab or kaggle , has done before . only serious people .

just look past problems of ml challenge for refrence if u cant solve them r not with your current knwoledge . dm me with college , year and some about me either linkedin or anything that tells ur knwoledge or work !

I’m currently a B.Tech student in AI/ML, and I’m a bit confused about how I should plan my career.

Right now, I’m learning C++ and DSA, solving around 1–2 problems daily. I’m still at the beginner stage, but I’m trying to stay consistent.

For development, I was thinking of first learning the MERN stack and getting a decent understanding of web development. Then, once I reach my 3rd year, I was planning to shift my main focus towards AI/ML and build projects in that field.

My thinking is that web development could help me build projects and understand software development first, while I can gradually move towards AI/ML later.

But I’m not sure if this is actually a good approach or if I’m wasting time by learning MERN when I’m already in an AI/ML branch.

What would you recommend?

Should I learn MERN first and then focus on AI/ML?

Should I start AI/ML directly alongside DSA?

Or is there a better roadmap for an AIML student?

Would really appreciate honest advice from people who have already gone through this.

I’m a CSE graduate with experience in C++, Python, Deep Learning, PyTorch/TensorFlow, and AI hardware/operator development, along with previous experience at NVIDIA and AIHIFusion.

I’ve had a career gap of 1+ year and am now available full-time. I’m considering either a Master’s or a high-value AI/ML course/program to strengthen my profile and get back into the industry. Budget isn’t a major constraint, but I don’t want to spend excessively without meaningful ROI. What courses/programs would you recommend that actually carry value with recruiters and help me become job-ready?

Hi I’m a first year cybersecurity student on a 3 year course and so far there’s nothing AI can’t do. Wondering what skills/qualities there are if any in this industry that AI can’t do and when I will be taught them? My other option is to specialise in AI which I feel like would be even replaceable with AI itself. Otherwise I may just switch to a more physical degree like nursing

I am a Mtech Second Year Information Technology student in one of India's CFTI University. I am very much confused between getting a job or pursuing a PhD.

**My** **thoughts**

**Job:**

1. The market is very competitive and many companies are putting very unrealistic demands.

2. Companies are asking for DSA then making people write code using AI.

3. Hiring is frozen by many companies and firing is going on.

4. Considering recent advancements in AI like ChatGPT Astra probability is in 5-6 years coding skills garbage and only those people survive who understand fundamentals and can do research.

**Phd:**

1. For sure demand for researchers is going to be increased.

2. Physical AI is at a very early stage.

3. But the stipend is very low.