Hi,
This git contains the exercise for your DS course, it is based, mainly, on the Kaggle's micro courses but was converted into regular Jupyter notebooks and all data is self conatined.
First thing you will have to do is clone this git into your computer, if you are not familiar with cloning (or git in general), take a look here, once you have done that you should have all needed files in a local directory.
Second you will need to install Jupyter Notebook (if you don't have it yet) and open it, if you need any guidance go to the docs. Once Jupyter is up and running, use it's file explorer to find the excercise notebooks in the notebooks directories under each subject.
Complete the notebooks by adding your answers (short to say, long to do :)) don't forget to hit save every once in a while. Once the excercise is done, download it as a notebook (.ipynb) file and email it to your instructor.
Currently there are 3 subjects:
- Pandas, questions dealing with data manipulation and analysis.
- Visualization, create plots (using Matplotlib or Seaborn, your choice, except for a couple of Seaborn specific tasks) and answering logic questions based on their understanding.
- ML, Basics of Supervised ML