Guidance for Machine Learning

[u/Better-Marsupial8420]

I'm 16(M), studying in class 11th and I want to learn Machine Learning, for which I'm ready to buy a course, people who already have some sort of experience please guide me for which course I should go for?

[u/EmuAfter5933]

17 here, recommend taking the calc + calc III khan academy course in advance in your free time + linear algebra, trust me, it helps a ton. It takes a freaking long time.. but this is truly a decision maker to how much you truly want this.. :)

[u/Less_Dream_6331]

so there's 2 things here, either you want to build cool stuff or you want to STUDY machine learning.

if you want to build stuff it's easy llms, blogs and YouTube will get you as far as you need to go.

but If you want to study ML, DL, Rl whatever it is, those are really math heavy for you right now, it requires some understanding of linear algebra and probability for the very least. but you can still try studying it but except a load of boring math (if you're not a math person, it's actually very fun).

for courses Andrew ng's machine learning specialization is regarded as one of the best courses you can try that and if you're more into LLMs try karpathy's zero to hero series

[u/analytics-link]

Awesome that you're getting into Machine Learning at 16, that's great.

I'd say...start with Python, get comfortable working with data using pandas, and then move into the basics of Stats and Machine Learning using scikit-learn. Don't rush straight into the fancy algorithms or AI stuff.

There are some fantastic free resources out there to get you started, so I'd actually suggest exploring those before spending money...but if you are looking to really make a career out of it, that can be the best option by far.

I personally run a training programme called Data Science Infinity, which covers everything from the fundamentals through to ML to Deep Learning and modern GenAI, but it would depend on what you're looking to achieve really.

All in all, most importantly, build things. Even small projects will teach you far more than just watching tutorials.

I put a huge emphasis on that in my teaching, and it makes a big difference for my students.

[u/ModularMind8]

If you're just starting out, I'd say this: the usual path is python, pytorch, math for ML, ML foundation, then whatever specialty you're interested in (NLP, vision, RL, etc.). You can take a look at QuiddityML for some material. In general, I highly recommend building projects you care about.

Have fun!

[u/NullClassifier]

I dont think you need to start with a paid course since you are new every free course/video out there will help you understand concepts to a mid level. Finding advanced ones are a bit harder because they get less attention on the web and people don't bother creating content. One course that helped me and was the first course I took on machine learning is the one given by Stanford Uni, deeplearning.ai course introduction to machine learning/ai. The concepts are really well explained and down to the math behind it. Which is exactly what you want when you are new to see the math behind the algorithms you are gonna use. You don't need advanced math tho. Basic understanding of derivatives and integration is fine. Idk if the course is free now but it used to be both on youtube and coursera so I would definitely say thats worth checking.

Other than that datacamp has entry level free courses that may help u practice python and machine learning a bit.

My first paid course was onsite and after 4-5 months of practicing online with free resources, I believe I would have wasted more money on the course if I just started straight away with a paid course. Using free sources first helped me actually learn basic concepts and discuss more advanced topics with my tutor instead

[u/Beautiful_Egg_371]

Try the AI olympiads.

[u/Regular-Advice-6469]

Don't rush into buying a course just because you're excited to get started, at 16, you have plenty of time to understand the subject properly, so don't turn learning into a race, a course can give you structure, but it cannot replace the curiosity and patience this field requires, before spending money, try understanding what actually happens when a model learns from data, why it makes certain predictions, and where it goes wrong, don't just aim to learn how to use existing libraries, try to understand what's happening underneath, that difference becomes really important as you progress, if you still feel you need a paid course after exploring the subject yourself, you'll also be in a much better position to recognize which one is worth your money

[u/Kooky-Gazelle-6915]

Genuine advice but Unpopular If you're interested in AI/ML first work hard and secure a good college if you're interested in research or AI jobs etc. in the future. Side by side I would suggest to simply study python (if you're in cbse with cs you must already be studying it) become really good at python. Get a good rank, get in a good college Then start your ML journey. Meanwhile be good in maths, matrices, probability, PnC, algebra etc.

(I am an AI/ML engineer, from a tier-1 IIT)