>>11026307First up review basic Linear Algebra, Calculus and Probability Theory.
Then learn Linear Regression and Singular Value Decomposition if you didn't already include this in your Linear Algebra review.
Next up Logistic Regression and its extension to (Deep) Feed-Forward Neural Networks.
Then you need to decide if you want to look at different ML techniques or if you really just need Deep Learning stuff.
If ML: Decision Trees, basic unsupervised clustering methods (KNN), Gaussian Mixture Models, Support Vector Machines.
If DL: ConvNets, Recurrent Neural Networks, LSTMs, (Variational) Autoencoders.
If you spend the whole month doing just this you can possibly get to a level where you can fake knowing some stuff fairly good and then hope to have the time to learn while doing.
