My first questions would be: are you currently studying for your CS degree? If so, see what classes are offered relating to Data computing/analytics and machine learning. Machine learning is a mesh between a computer scientist and a mathematician where you use statistical and probability along with code to run through large amounts of data to gain information from data given. From absolute zero? Linear algebra, statistics, and probability are a must. Python has great libraries to start out. Libraries like pandas, numpy, and scipy/scikit for machine learning are what's used, but understanding what the built in functions are doing are important. Understanding how to normalize and cluster data when it's uncategorized is just applying lots of math at the end of the day. Having a background as a software engineer first can help as it gives merit that you know how to build and test code, but sometimes that has less focus on understanding numbers, cleaning data, and testing/training and modeling algorithms for ML/AI.