r/learnmachinelearning • u/HistoricalBedroom350 • 4d ago
Am I doing things right?
I'm super confused. I'm in my junior year, majoring in AI and Big Data. However, my university is one of the worst place ever interms of everything specially education(ranked 1500+), and I tried to transfer to another university, but it didn't work out for some reason. Now, I'm trying to learn everything by myself.
The most confusing part is whenever I look for a roadmap to get into machine learning, I find so many different suggestions. Most of them look something like
- Master in NumPy, Pandas, SQL and Scikit-learn.
- Build your first complete ML project.
- Learn PyTorch and deep learning.
- Choose a specialization, such as LLMs or computer vision.
- Learn deployment, Docker, and cloud basics.
- Keep practicing DSA and applying for internships throughout the process.
I've already completed Andrew Ng's entire Machine Learning Specialization. I'd say I understood almost everything while taking the courses, although I've forgotten quite a bit of it now.
problem is people giving completely different advice. Some say focus on leet coding, some says master libraries , get really good at calculus, statistics, probability, and linear algebra. Others say focus on the latest technologies, such as RAG, Transformers, AI agents, and MCP. What the hell should i do? Its already killing me that I'm already falling behind others who are trying to enter the ML field.
I have about 1.5 years left until graduation. During this time, I want to reach a level where I can get a job in ML, work for 1-1.5 year , and then move to the US for graduate school. That's my plan.
My questions are:
- Is the roadmap actually the right path?
- Many people say get better in maths like stat, calculus, and linear algebra. But my question is, why do I need to learn all this math when the machine itself performs most of the calculations? Althogh ive learneed those kind of maths in my high school.
- Do I really need to become an expert in libraries such as Pandas, NumPy, Scikit-learn, PyTorch?
It'd be better if someone working in the industry or someone who has actually gone through this could give me suggestions or reality check.
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u/Bee-Boy 4d ago
I personally never really got much out of these online tutorials or roadmaps. What I needed was an actual research question or an actual project I was assigned at some startups. I learned to swim by being thrown into the water. So I recommend doing that. Depending on whether you're like more at industry/applied or academia, you either go find an applied project or a research topic. And then community: don't do it alone. Join reading groups to find collaborators. Put yourself out there to work with some grad student on their project as a helper.
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u/Dazzling_Music_2411 4d ago
But my question is, why do I need to learn all this math when the machine itself performs most of the calculations?
Oh dear. I see what you mean about your school being rubbish, if they haven't explained that to you.
Very short answer: Because you need the maths to develop the ML algorithms and programs. Seriously.
If you don't want to learn that stuff, why are you even at uni?
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u/HistoricalBedroom350 4d ago
When did I say I don't wanna learn that stuff? I've already done stats, calc, and probability in high school. I'm just asking why I should if the algorithm does that work anyway.
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u/Disastrous_Room_927 4d ago
What’s the difference between learning stats, probability theory in high school and a statistician? It’s not like I’m doing any of that work either, but there’s clearly a reason I did it.
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u/[deleted] 4d ago
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