How to handle words not in the dictionary (while finding similar words)?

I am doing a project on Semantic text analysis where my data has column Technical skills (so I have to train data to find similar words) which are words and not sentences. So I wish to find similar technical skills when I pass a word. I am aware of using Word2Vec and Glove. My issue is that if I pass for example Pyton which is actually (Python). So since the misspelled word is not in the trained words it will show error (saying that the word is not in the dictionary). But I want my model to understand that the misspelled word is Python since it is closer to it and give the output.

So please suggest me or give me some insight on how do I solve this (how can I approach this problem).