What are the steps and correct order of the operations in Machine Learning? [from Getting data to optimising models]
Yes learning online from different tutors can lead to different strategies. But this stats that the flow depends upon the type of data. Not everytime you have to create features or deal with outliers. 

In case of images you reduce noise by applying different methods &amp; filters, in case of text you remove stopwords, punctuation etc. So it depends upon data &amp; its amount. General way to proceede for me is as follow


Understand definition &amp; get domain knowledge
Gather data
Pre-process it (Involves removing noise, applying transformation, pruning data etc)
Do feature selection if necessary
Do data visualisation
Do different model experiments with sample data.
Fix 2 3 models for case
Train with real data
Use different matrices to evaluate (depends upon the data &amp; definition)
Make model accessible using API/Direct to client


This is how in industry i have seen everyone around me works &amp; i follow the same. Has helped me but this is way general, here you have much to change based upon definitions &amp; tasks.