Regarding Steps 1, 2 and 7, I think you don't have to do it if you don't have time.
-Acquisition of Statistical Test Level 2
-Overview of Gradient Descent Optimization Algorithm
-Implement gradient descent with full scratch
-Implement kNN with full scratch
-KMeans algorithm and how to operate SVM
-Visualization of kNN, SVM, XGBoost
-Gradient Boosting and XGBoost
-XGBoost taught by Kaggle Master
-Brush up your decision tree skills
Another thing I would like to mention is
And so on. (I will add it in the future)
-Intuitive understanding of Deep Learning by removing neurons
-Introduction to NLP written by legendary Peter Norvig
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