labSyllabus.md

Lab syllabus

1. Introduction to Python
   1. Installing python
   2. Chosing an IDE
   3. Jupyter notebooks
   4. Importing libraries
   5. Basic arthmetic
   6. Basic data import
   7. Basic markdown
   8. Basic git and github
   9. Project: Cloning a github repo, creating a jupyeter notebook, adding it to version control, reading in a dataset, performing a basic manipulation, commiting changes to git, pushing changes to github.
2. Tour of programming in python
   1. Control flow
   2. Data structures
   3. Creating functions
   4. OOP concepts in python
   5. text processing
   6. Project: write a basic prediction function using thresholding and MRIcloud values.
3. NumPy and matplotlib
   1. Plotting in python
   2. Arrays and mathematical data structures in python
   3. Project: creating an 3D array of MRIcloud imaging data. Performing a simple statistical summary across one dimension of the array. Plotting the result.
4. Pandas
   1. Data manipulation and cleaning
   2. Project: reading in MRICloud text data; putting it into a pandas dataframe. Performing data wrangling on the datarfame. Creating numerical summaries and exploratory plots.
5. Pytorch, Scipy
   1. Regression, linear and generalized linear models in python
   2. Setting up pytorch
   3. Pip and conda.
   4. Project: prediction Alzheimer's disease status using the ADNI database.
6. Lab on running deep networks in python
   1. Project: convoluational neural network for lesion segmentation.
7. Lab on running deep networks and evaluation
   1. Project: evaluation of a NN algorithm for "Early Prediction of the Impending Onset of Septic Shock in Patients with Sepsis."