It really depends on how deep you wanna go. Folks get PhD on it. But at the same time, depending on your application of interest, you can learn a lot of practical concepts just by doing some Google search.
For example, I suggest learning Fourier Series and Fourier Transform, Wavelets, and Sampling Theorem (Aliasing, Nyquist-Shannon).
Also ThinkDSP is an amazing hands on book that goes over all you need and making it easy to understand (most of DSP books are very 1900). Also available free online.
https://greenteapress.com/wp/think-dsp/
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This is a good course if you wanna learn coding aspects of it in mostly Python with ML applications (chapter 4).
https://www.coursera.org/learn/advanced-machine-learning-signal-processing?ranMID=40328&ranEAID=SAyYsTvLiGQ&ranSiteID=SAyYsTvLiGQ-w7rGhIThTD57y_MUlUsCVw&siteID=SAyYsTvLiGQ-w7rGhIThTD57y_MUlUsCVw&utm_content=10&utm_medium=partners&utm_source=linkshare&utm_campaign=SAyYsTvLiGQ#syllabus