Applying random forest model to a dataframe with multiple types of data
One thing to remember when we use Random Forest is when you use a categorical feature for training it shouldn't have more than 53 categories. Sometimes RandomForest takes numerical data as categorical. To overcome that make sure to convert all categorical as factors using this command.

df['col_name'] = df['col_name'].astype('category')


Lastly, make sure that all the levels in a categorical feature are presnent in both train and test data or else the model cannot hadle such situations.

I think you might get the model running if you can use any server(as the model can use the servers processing capacity to its fullest) and deploy on that and let it run before you leave for the day, before deploying make sure that you have tested the code on sample data. So, that it won't abend with some error.

Do let me know if you need any additional information.