Deep learning v.s. machine learning course: which one to start?


I am new to AI. Which course should I start with: Machine learning or Deep learning? They look both interesting and both taught by Andrew Ng.

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Hi @supercobra,

You should take Machine Learning specialisation first to fully understand and appreciate the Deep Learning Specialisation later on, as DLS concepts are built on that.



You should start from Machine Learning.

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And should be learned Deep Learning after Machine Learning at all?

That’s a great possibility if you want to learn or apply deep learning, see also this thread: How to become an AI Engineer - #4 by Christian_Simonis

One of our mentors @saifkhanengr published a nice outline on LinkedIn how a possible course sequence can look like: check out this post!

Best regards

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I see that there are a lot of topics that say about Deep Learning in Advanced Machine Learning already. I would like to know, through how many of lessons of Deep Learning I would able to jump after ML? Or will it be completely new information?

Deep Learning Specialization (DLS) will jump more deeply into the topics discussed in Machine Learning Specialization (MLS). Furthermore, DLS covers a wide range of topics (that didn’t discuss in MLS) and some general guidance which is necessary for any machine learning engineer to know about.


so, how many can I jump over? I would like only plan the time of course learnings

Having taken MLS does not mean you can skip any of DLS, if that’s your question. Prof Ng presents all the material in a more advanced way in DLS, so you should start from Course 1 and not skip anything.

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Exactly, this is also my take. Thanks @paulinpaloalto for the hint!

I just found that all this and I think more videos in the future will be near the same to Machine Learning course (with better content in ML course by the way).

So, is this exception? Will all other future video be with unique content?

Let me give you an example. In high school, in every class, we studied Math, right? So, my question is: studying math in first grade can make us experts to skip math in second or third grade if there are some same concepts?

So, if you want to skip some videos, do it at your own risk. If Machine Learning Specialization is first grade, then Deep Learning Specialization is tenth grade (in my opinion).


I just saw all week 2 and can say that there is everything the same as in ML course (on 90%), except introduction of derevatives. And if I understand correct, I even don’t need this all calculus in practice, because functions from frameworks will do this operations under themselves.

So, all week was only about logistic regression will work faster with derevatives. Even broadcasting was explained in one of optional ML videos, as I remember.

OK. If you feel comfortable with skipping some videos. Though I do not recommend that.