Machine Learning is powerful, but it’s not the only skill you need to succeed! In this video, we’ll explore an alternative approach that could be more practical and impactful for your career in tech. Learn what skills are becoming essential in the modern data-driven world, and why you might want to shift your focus. Don’t miss out on this eye-opening perspective!”

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38 thoughts on “Don’t Learn Machine Learning, Instead learn this!”
  1. I'm 18, finished my 1st Engineering School year, even got 1st place in promo, I am a generalist & passionate in CS too so I decided to try specializing on my own, this summer I chose DS,ML,DP,AI y'know all the acronyms but sometimes later during my journey I got struck: path is so long (there's that video of levels of ML that exposes the complexity of the field in 5 levels and I'm not done with level 1 yet + diff grows exponentially), recruitment is narrow and you explained it yourself, adaptability is too frequent everyday new researches and breakthroughs are made and they aren't the simplest things around so you gotta study daily these news and eventually catch up
    So I decided to lean on Generative AI & Automation… Which is pretty easy till now and continue Full-Stack and maybe on Vibe Coding too at some point (those LLMs are evolving way too fast, so gotta gain time)

    I will still learn for the love of knowledge but my priorities got a massive blow

    Also, my Engineering School offers as specialities DS & AI, Cyber Security, and IoT, I'm interested in all 3 but actually can't choose so any recommendations out there ?

  2. I have done backend, made few projects too, now recently started ML So what do you recommend to do ML as much as I can or do DevOps and do more projects on full stack side

  3. @Deepchanddc2 is it possible to become a ai/ML engineer with a +2 background and without a cs degree but proper ML knowledege ,maths and core ML concepts
    PLEASE REPLY

  4. You must go through the process of training the mind. It doesn't matter if it will be automated. It's about the mind. Now there’s a paradox (this also applies to IT studies- they should be completed; of course, knowledge itself has no value, but the process of acquiring it shapes the 'scientific mind,' meaning that the process of gaining knowledge becomes a tool, not the goal itself, and that's why Jensen is wrong not to teach programming; an analogous problem- but in the opposite direction- occurred with Pascal, when after mathematics he turned to philosophy; he couldn’t think like a philosopher because he didn't have the 'philosophical meta-mind').

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