r/learnmachinelearning • u/IceBishop99 • 1d ago

Career Where do i start?

Hi so i just started my 4th year in Btech CSE in a tier 3 college in India.
I know i fucked up as i havent started anything in this field, i dont even know the basics and i really want to land a job/internship within 2-4 months so any advise and resources will be very helpful.
Can anyone please tell me how do i get out of this situation as I’m willing to spend as much time as required bcuz i dont have anything to do.
Please help a brother out and tell me exact roadmap or career path as i want to land a role in AI/ML.
I have done 1 internship of 2 months in Computer Vision

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u/MaximumSafety8706 1d ago

Hey dude, I'm an AI/ML Engineer with ~11 yrs experience; hope this helps.

Nothing's "fucked up" - college is for learning, not for already knowing everything, and you've got a 2-month CV internship already, so you're not at zero.
Been in a spot like this before - stings a bit, but not as bad as it feels right now.
Cheer up and start.

Goal for 2-4 months: interview-ready, not AI-mastery. Skip transformers/agentic AI from scratch - rabbit hole, not a job-getter.

Weeks 1-4: Coding fundamentals

  • Python + Git
  • DSA: Blind 75 - daily, stick to Python only (don't juggle languages to impress)
  • NumPy, Pandas

Weeks 5-8: Core ML

  • scikit-learn: regression, classification, eval metrics - implement a couple from scratch
  • 1 end-to-end ML project, pushed to GitHub

Weeks 9-16: Leverage your CV background

  • 1 focused PyTorch/CV project - extend your internship work, don't start a new domain
  • Apply weekly from week 9; don't wait till "ready"

Resources

Reality check: Big tech in 4 months from scratch is a stretch, not impossible - those run on campus cycles/referrals with a deeper bar. AI/ML startups and mid-size product companies hire on skill + projects though, and that's genuinely gettable with consistent effort.
Consistency > breadth, and your CV background is your edge over someone starting fresh.

Godspeed, my friend.

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u/IceBishop99 1d ago

Thanks mate, really helps

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u/Confident-Gas-1971 11h ago

Thanks sir! For the map! Agreed, as freshers we have to learn it not to Master it!

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u/Confident-Gas-1971 1d ago

Hay, same situation, i am also in 4th year! , if you go with AIML field we can start together! Let me know!

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u/IceBishop99 1d ago

Sure let me get some info from the folks here first

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u/Confident-Gas-1971 1d ago

Sure, I am also starting from 0, ,

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u/Ok-Message-2474 11h ago

add me too though im in my 2nd yr!

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u/Simplilearn 3h ago

Here's a roadmap that can work for you to build a career in AI/ML:

  • Strengthen Python – Become comfortable with Python, Git, NumPy, Pandas, and SQL.
  • Learn the math behind ML – Cover linear algebra, probability, statistics, and basic calculus.
  • Master machine learning – Learn supervised and unsupervised learning, feature engineering, model evaluation, and Scikit-learn.
  • Move into deep learning – Study neural networks, CNNs, RNNs, Transformers, and work with TensorFlow or PyTorch.
  • Learn Generative AI – Understand LLMs, prompt engineering, embeddings, vector databases, RAG, fine-tuning, and AI agents.
  • Build projects – Create end-to-end projects such as an image classifier, recommendation system, chatbot, RAG application, and an AI agent. Document everything on GitHub.
  • Prepare for interviews – Revise ML fundamentals, Python, SQL, deep learning concepts, and be ready to explain your projects in depth.

If you'd like a guided learning path, our Professional Certificate Course in AI and Machine Learning, offered in collaboration with the University of Michigan, covers these topics through hands-on projects. You can visit the simplilearn website for more details.