I have a dataset that my instructor provided from a company, and I was asked to prepare it for machine learning.

There are several missing values in the dataset, and I am unsure how they should be handled or imputed. I am also unsure which standard practices or workflow to follow for machine learning data preparation. Although I conducted my own research, I was unable to find sufficiently clear or satisfactory guidance.

Since this is my first time performing a full data preparation pipeline, I would appreciate guidance on how to approach this process correctly. Any recommendations for reliable learning resources or references would also be appreciated.