Yes, I fully agree with @xztt wrt this Springer Primer - that’s my favorite book on this topic. I believe also “Sensitivity and Uncertainty Analysis – Volume I – Theory”; Dan G. Cacuci; Chapman & Hall/CRC 2003 [link] and “Sensitivity and Uncertainty Analysis – Volume II - Applications to Large-Scale Systems”; Dan G. Cacuci, Mihaela Ionescu-Bujor, Ionel Michael Navon; CRC Press 2005 [link] could be to your interest as well. If you plan a trip into ai/ml/rl: “Stochastic Learning And Optimization - A Sensitivity-Based Approach”; Xi-Ren Cao, Hong Kong University of Science and Technology; Springer Science+Business Media 2007 [link] and “Sensitivity Analysis for Neural Networks”; Daniel S. Yeung, Ian Cloete, Daming Shi, Wing W.Y. Ng; Springer-Verlag Berlin Heidelberg 2010 [link]. In my opinion, it should be noted that there is a lot going on in the fields closely related to quantum computing that in about 5 years (more probably in 10 to 30) could completely change the perception about the subject of sensitivity analysis. However, as for now, there are almost no books on those topics and most of the things are in lengthy papers that, as far as I know, are regarded as dangerous even by persons skilled in reading various advanced notations. BTW, I also believe that even not straight about discussed subject a book “Chaos: Making a New Science” by James Gleick [link] and some short videos like Educational video (3b1b style) on chaos or Educational video (3b1b style) on chaos - #9 by j_u could make a time enjoyable for a person with a curious mind. And of course some of the local posts by @ChrisRackauckas I am finding interesting (but usually more advanced that my current coding skills). However, my perception is [first hand knowledge dated a few months back] that he is not that easily approachable.