You can start by learning more about basic scientific libraries such as Numpy for working with arrays; Pandas for data manipulation and analysis; SciPy which contains modules for optimization, linear algebra, etc. in youtube channels; after them, I suggest you start reading "Introduction to Machine Learning with Python: A Guide for Data" by Andreas C. Müller and Sarah Guido. This book contains various scientific tips.
This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming.
Book Introduction to Scientific Programming with Python