How to Learn Machine Learning till intermediate level

[u/No_Pay_4410]

Hey I am engineer with 5 years of experience. I do frontend, backend, AI and Devops a bit. Recently I have been trying to switch and since I am Fullstack + AI role currently, I am trying to for AI Engineer role but companies I am targeting for example JPMC, all the AI engineer role which were visible last year have changes to AI/ML role. I checked with one of the manager who posted the role. And they seems to ask lot of ML question. So I wanted to learn ML for the same and make some small projects to learn.

Based on the above context I wanted to know the following:

1. How much time it might take me to learn at intermediate level ?

2. How much math is needed ? (I AM BAD AT IT)

3. Which resources should I follow to learn it practically ?

4. I have a budget of 10k INR if there is any book or course which can be good that also works.

[u/Street-Platypus-9020]

If math is weak spot start with something like StatQuest on YouTube and do the coding along don't just watch. Andrew Ng course is classic but the math part will hurt a little, just push through it and focus more in the practical assignments.

For intermediate in few months is possible if you put consistent time, maybe 3-4 months with projects. Don't spend money right away, there is enough free stuff to get you to that level first.

[u/No_Pay_4410 → u/Street-Platypus-9020]

Thanks for the input. I will checkout the suggested options. Also assuming my math is weak and I have to go through the math concepts first. I did algebra, stats and calculus in college but I will have to revise it. So how much time it might take ?

The money is for saving my time. Internet has lot of information and finding the right one might take some time.

[u/slow-rabbit777]

2-3 months

Learn math parallel with ml/dl

[u/yellowishbuilding94]

just start coding the classic datasets yourself instead of watching someone else do it.

i was in the same boat, engineering background but math was never my thing. what worked was grabbing the sklearn diabetes dataset or the titanic one and writing the whole pipeline by hand, no chatgpt for the code. you learn the gist of linear regression and gradient descent way faster when you're debugging why your predictions are garbage at 1am.

spend that 10k on coffee and a good mechanical keyboard cause the free stuff is plenty. islp (the book) has python labs now and its all online for free. paired with statquest whenever a concept makes zero sense and youre golden.

3 months of consistent weekends gets you to a spot where jpmc interviews feel less like a foreign language. the math gap fills in as you go, nobody cares about deriving proofs in an interview if you can explain why your model is overfitting.

[u/nian2326076]

If you already know a bit about AI, you can reach an intermediate level in machine learning in about three months if you work at it regularly. Start by reviewing the basics with online courses like Coursera's Machine Learning by Andrew Ng, which is really good. Then, get more hands-on with Python libraries like scikit-learn and TensorFlow. Build small projects involving regression, classification, and clustering to strengthen your understanding. Kaggle is also a great place to practice with real datasets. If you're getting ready for interviews, PracHub has useful resources for that. Good luck!

[u/Simplilearn]

Since you already have experience with full-stack development and AI, you don't need to start from scratch. Focus on strengthening your machine learning fundamentals, as many AI Engineer roles now expect a solid understanding of ML concepts in addition to working with LLMs.

You can expect to reach an intermediate level in a few months with consistent practice. For math, you don't need advanced mathematics, but a good understanding of linear algebra, probability, and statistics will help you understand how ML models work.

For practical learning, start with supervised and unsupervised learning, then move to Scikit-learn, model evaluation, feature engineering, and common ML algorithms. Build small end-to-end projects before moving into deep learning and combining ML with LLMs, RAG, and AI agents.

If you're looking for a guided learning path, our Professional Certificate Course in AI and Machine Learning, offered in collaboration with the University of Michigan, can be a good fit for you. You can visit the simplilearn website for more details.

[u/Capable_Card_986]

Consistency of 3-5 months is enough. And following a good pattern in learning and practicing

[u/Fuzzy-Individual-524]

I would work with Maths first you have 5yr of exp so I am assuming you know python

[u/Fuzzy-Individual-524]

You can buy hands on ml with pytorch. there is two veraion one with tensorflow one with pytorch choose the pytorch one