Please review my sketch of the Machine Learning process
This process will result in data leaks. The split needs to happen earlier. Normalizing data before the split means that your training data contains information about your test data. I would put the split at 3. in your flow chart.

A common step I think you have missed is imputation of missing values. I would put that before feature engineering.

Overall I think this is a good rough outline for a beginner to follow. It is overly simplistic and leaves a lot out, but I think you know that and you have to start somewhere.