What to learn system design or AI+ML?
Posted by aimless_hero_69@reddit | learnprogramming | View on Reddit | 12 comments
Hi all,I am about to enter in 2nd year ,so by 2029 which one to learn ?which one helps me to get more offers in this AI growing days?
JadeedX@reddit
Learn both, but start with system design first because it helps you understand how real-world applications are built and is required for most software engineering jobs. After that, move into AI and machine learning since they are growing fields with high demand, but they work better when you already understand how systems are structured. By learning system design first and then AI/ML, you will have more job opportunities and stronger skills by 2029.
Simplilearn@reddit
A safe and effective path right now is: Start with programming and problem solving, then move into one solid direction like data, AI, or software development. After that, build real projects so you can show what you can actually do.
In AI-heavy roles, what stands out is knowing how to work with data, build models, and explain results. In software roles, it’s about building systems and applications. So instead of picking one trend, focus on a stack like: programming + data handling + one specialization + projects.
If you want a structured direction, you can explore our free beginner-friendly courses on AI and Machine Learning to get an understanding of fundamentals with practical learning.
wanderfflez@reddit
Probably better suited for r/cscareerquestions , but to answer your question: I think if you're doing Bachelor's then probably neither yet at least for 2nd year.
When starting out instead of going directly into System Design or AI/ML unless your degree is about it, then I'd focus on building projects and building up the instincts/understanding best practices. From there you can then do System Design after you understand more about why system design works and how it actually is applied. System Design is usually more for Mid - Senior Levels and are rarely expected from entry levels.
For AI/ML, while this is a 'hot' topic, actually working with ML Engineering requires way more than just a Bachelor's I believe. Typically at least a Master's, it's also more complicated than just integrating ChatGPT (Which would be AI engineering). I'd say look into the companies you'd want to work/get internships in and build stuff using their stack.
Once you've understood the stack itself, start working with the systems in a larger scale with distributed systems for example.
Vault_Tec8@reddit
You make a solid point about focusing on building projects first. It’s essential to develop those instincts before diving into System Design, especially since it’s geared more towards mid-level pros. Balancing practical experience with theory really sets you up for success in the long run!
my_life_coding_chaos@reddit
thanks for
aimless_hero_69@reddit (OP)
,?
PalpitationOk839@reddit
Start with system design and core fundamentals first. Once your base is strong and runable, you can explore AI/ML on top of that
Educational_Employ52@reddit
Both, but start with system design. AI/ML tools change fast, but if you understand how systems work — how things connect, how data flows, how to build something that actually runs — you'll be able to use any AI tool effectively. I started learning programming 25 years ago with no CS background and the thing that helped me the most was understanding how things work under the hood, not chasing the latest trend. AI is a tool, not a substitute for knowing how to build things.
Specific-Purpose-227@reddit
If you decide to learn AI ML try following this roadmap. https://github.com/bishwaghimire/ai-learning-roadmaps
OnionQueen_1@reddit
thanks for this
Ok-Pause-6599@reddit
Bro you should know core python and it's libraries like pandas, numpy, and matplotlib. after that you should do dsa from python and After that DBMS(database management system) after a lot of practice of all concepts now you are able to start machine learning after that core ml then deep learning then deployment. That's all...
thequirkynerdy1@reddit
If you have a few years, why not learn both?
For this response I'm going to assume:
* By system design you mean distributed systems (there's also how to structure clean code).
* By AI/ML, you mean creating AI/ML models as opposed to using LLMs either in products or to help with coding.
If you meant one of the other things, let me know.
Distributed systems are more useful at medium to larger companies where you have to scale to a large number of users. It's also common in mid to senior level interviews, but for getting a first job you *probably* don't need it (can't promise some company won't ask about it though). However, it's very useful if you do work at a medium to larger company for understanding how the tools work under the hood which in turn lets you write more efficient code.
AI+ML is used in data science-y roles where you need to analyze large datasets to provide some kind of insight - think ads, recommendation systems, finance, etc.
They also have different prereqs:
* Distributed systems requires some knowledge of computer systems. You don't need to know deep computer architecture, but you should know say why disk access is different from RAM access, why networks can be faulty, etc.
* AI/ML requires (if you want to understand the models beyond just calling an API) linear algebra, enough calc 3 to define a gradient, and a bit of probability. You probably won't need to do pen-and-paper math, but you do want to understand say how gradient descent and common refinements work so you can tune if needed.