Hi ayush, can you explain how to get a machine learning or data science remote job in a western country having just a college degree and no working experience?

Sir I really want to take some advice from you please please will you give me some of your precious time If you have an instagram id for your follwers then please I want to connect with you and want to take some little advices please

Ūy vi

Hi Ayush can I do machine learning with low math skill I know that answer in No but I thought you have experience in data science and machine learning soo

Hey bro can you take another I want to start my journey and need guidance

Bro, can u guide me how to learn n get a job in this field please ? I wanna learn ML and get a job

Hahaha , even my job interview consisted of the same questions. I just joined as an ml data associate in amazon.

Hi can you tell us about what questions you were asked ?

​@@dhruvarjun5Hi, did you do any projects before applying ? Can you please tell us about your interview?

​@@zenitsuagatsuma6894 hey did you find an answer?

Thanks a ton

Start with data analysis then python, statistics, linear algebra, calculus, big data, cloud, git, machine learning and deep learning by Andrew ng

@@dpsy7574 I wish that was enough :)

Noted

​@@AyushSinghShplease Hindi mein banaya

​@@AyushSinghShplease as soon as possible 🙏

​@@MohdDanish-wf3krbro not many can understand Hindi 😢

Let it be in English

Hi Manoj, I actually have proper roadmap on AI&ML, Data Science and MLOps on my youtube channel, do consider checking it out :) also I don't have good experience in data engineering, so my advice won't make any sense.

Not possible to replace data science in just 5 years. I think it may take more than 50 years if there will be so much advancement in AI technology. according to current situation you don't think about this get start to learn all of these stuffs.

it may take with the launch of github copilot update

@@BlockWithBadhautiya well the growth in tech is exponential and not linear so even 5 to 10 years is a very very big time considering the advancements in quantum computing added to it

Hi - I'll be launching my course very very soon, good things takes time :D

😂

Completing titanic project makes your progression maybe 1 percent increase, this has become very long journey and you have to dedicate at least 2 years to get into a job. The situation is very shit that almost like you must complete hard work similar amount to a college degree..

I am not joking@@FindMultiBagger

This and many more reasons, there are no junior Data science and ML jobs by 2023 I guarantee that

yes

I too have the same question??

I too have the same question??

Same doubt

Data science

go and checkout my channel and fcc channel, how many free courses I've added :DDD

You spoke my mind 😂😂😂.

@@AyushSinghSh. Your videos are good no doubt but even though you added free content please down play other there must be atleast 1% useful in other videos

@@stayhumble3245 sir, the free content is 100% useful but what I mentioned in the video is some of the mistakes which people should avoid and the market change scenario.

Wish I could understand your engrish

I think "yes", you will be able to get a job, here're some of the tips which I want you to keep in mind while learning AI/ML:- Fundamentals and core is the key, don't try to go with DL, NLP until and unless you're comfy with core.

Hi, Let me tell you, Andrew Ng is like a one of the pioneer in AI.His way of teaching is so clear and engaging that honestly, anyone who's keen to step into the world of ML should start with his courses. Now, about the basics of ML you mentioned. It's great you've got a handle on them, but it's important to remember that 'fundamentals' in ML aren't just a handful of topics. It's a vast area covering many things like formal models, Empirical Risk Minimization, Inductive bias, hypothesis classes, PAC learning, and so much more. These aren't just fancy terms; they are the pillars that hold up the entire structure of machine learning. My advice to beginners is always this: Don't rush into the deep end of Deep Learning until you're really comfortable with these fundamental concepts. There's a common mistake where beginners skim through online tutorials and believe they've got the fundamentals down. But there's a lot more to it than that. And talking about whether to start with Andrew Ng's courses now or not, my perspective has changed a bit. A year back, I would've said 'Yes' without a second thought. But now, I think it's more important to delve deeper into the essence of ML. Machine learning isn't just about algorithms. There's so much richness in every concept. Take the term 'learning', for instance. It's a whole universe in itself, way beyond what most online tutorials cover. So, if you're diving into an algorithm, don't just learn how to use it. Ask questions - What is it? How was it discovered? Why do we need it? How do you test and validate it? Understanding the core of these concepts is crucial. And once you've got a solid foundation, then you can confidently move towards more advanced topics like MLOps and such.

@@AyushSinghSh Thanks for explaining and giving a detail answer. Very few creator in ML space take the pain of replying in such details .

Hi, We are planning to launch my core ml course very soon! Thanks :)

​@@AyushSinghSh hey! Would it be on KZfaq?

I never said to not to trust free data science course, i just stated some concerns, there're tons of free courses which might give you kickstart but very less really talks about MLOps and I have tons of free courses haha :D

Thanks, data science is not for everyone though. Enjoy the work

Hey - Read books/articles on topics and then teach/discuss with others. Record yourself explaining concepts. Watch great teachers and observe their style. Write blogs explaining ideas simply. Speak slowly, clearly with concise sentences. Practice, practice, practice! The more you teach and discuss, the better you will become.

I think I use to checkout kaggle long back, but generally the advice which I give it to my students is to go to a competition which really interests you and select the best notebook and try to understand it and then further use that notebook and refactor it and productionize it accordingly.

Hm, You can certainly start learning data science and make a career transition, though it will require hard work, however try to play safe - like have a job and in parallel learn DS & ML. Start with the tech core - Python, SQL, statistics, Excel. Then go ahead with core machine learning concepts. Your non-technical experience will also be helpful. You have an understanding of customer service and business perspective. That will aid data analytics. So go ahead what your instinct says, as I heard from someone "there's nothing right decision, it's always lesser wrong decision"

yes, i'll, to answer in short, it's yes for companies who are mnc's and corporates and no for startups and also it depends on which role you're applying for, for example for the role of "software engineering - machine learning" will require you DSA but "data scientist" will certainly not for startups.

Keep it up

You learned Calulus, linear algebra, ec?? Just curious.

@@nitilpoddar Yes, learning Linear Algebra was easy, whereas I learnt just enough calculus like calculating derivatives and others

Mind blown!! @@HarshSingh-zp7jb

@@HarshSingh-zp7jb where did you learn from

Hi - I'll be launching my course very very soon, good things takes time :D

Omg😢

I am in a IT related job but if you are trying to break into this dont even waste your time, the market has become really garbage last year

@@deniz.7200 STFU. Did you dedicate 12-15 hours learning ML everyday? Most people will learn for 1-2 hours everyday . put in fucking 12 hours! Learn at the speed of 3x compared to everyone else and you can learn anything and everything. Make sure that nobody works harder than you! Make sure nobody learns at the same speed as you! Have some guts to become the best at what you do! Motherfucker