Where I’m coming from: I’ve some very basic ML exposure with Andrew Ng’s Machine Learning course. I think I’d like to prepare for Google’s TF certificate exam and take the exam by the end of this summer (end of August).
What I’m thinking of doing: I was thinking of implementing all assignments from Ng’s ML course in Python first, then do his Deep Learning specialization and then do Laurence Moroney’s course specifically designed for the exam. (This would probably take ~2 months if I give in 4-5 hrs per day, so I would still have ~1 month to do whatever you guys recommend.)
Is Ng’s ML course + deep learning specialization enough to start Moroney’s course?
Should I do anything else before taking the exam? (Kaggle competitions, projects, etc.?)
Thanks in advance.