[sumitgt]

I won't really comment about ML/AI in general. But, if you specifically care about getting into Deep Learning, I would say only bother looking into: - Basic linear algebra and matrix algebra.

Since you would rely on frameworks like Tensorflow to handle figuring out the derivatives for you, you don't really need to know much calculus. Just read up on what derivative of a function at a particular point signifies. This should give you enough intuition to understand things initially.

A skill that would really come in useful would be ability to look at a function and think how increasing/decreasing one of the variables would affect it's value. This would help develop intuition around a lot of concepts used in Deep Learning topologies.