I'm surprised that no one has yet mentioned Andrew Ng's Machine Learning course on Coursera and to go a bit deeper, his deep learning specialization on Coursera as well. Along with the programming assignments it's a solid way to get your feet wet. And definitely second the suggestion of the fast.ai courses as well
As somebody that has started learning AI/ML and was looking at the exact question here three months ago - I found the Andrew Ng deeplearning.ai Coursera course an amazing starting point.
It was high level enough, and got me to understand enough, to get me to a point where I could start trying to build a side-project, without exposing me to the deeper math behind Neural Nets.
It was a great starting point without being overwhelming. Now I feel that I have the option to either go deeper if I need to, or go wider.
I find Andrew Ng to be an amazing teacher - explains things simply, clearly, and in a way that I find super easy to understand.
I think fast.ai is the more "programmer-y" do-first-learn-as-you-need approach, and Andrew Ng's is the more "math-y" learn-basics-work-your-way-up approach, and they can work well together too.
This is true, but it's more than that: the fastai professors (Jeremy + Rachel) have studied how people learn. How teachers can structure courses to maximize understanding.
They believe (and have research backing them up), that the way we teach math (base and rote concepts, building until you can understand something complex) is sub-optimal. They dive into the code and get stuff done, then later bubble back up for concepts.
For me, it was bewildering at first, but if you can trust your instructor, you trust they won't leave you stranded. (It does also require the type of student who does a lot of study on their own!)
I took this course. Andrew is a great teacher. However, I wish he worked on his public speaking a bit. He has certain speech patterns, like starting sentences with "it turns out..." and after a while it becomes extremely irritating, at least to me.
