Overview
Welcome
Testing Welcome
Accessing Jupyter Notebook
Instructions on accessing jupyterhub
Introduction to Notebook and beyond
Introduction to features of Notebooks and python syntax
Introduction to Python
Description of Module 1
Python-Variables
Python variables and assigning values to variables
Python-Strings
Strings and string manipulations
Python-Numeric types
int, float and complex in python
Python-Operators
Manipulating inputs
Python-Loops
Run X times.
Python-in-practice
Advancing with python datastructures, functions and Exception handling
Python-Lists
Most commonly used sequence
Python-Tuples
Immutable list
Python-Dictionaries
Container of Key-Value pairs
Python-Functions
A block of organized and reusable code
Python-Exception-Handling
Representation of an error
Python-File-IO
I/O operations on files and standard I/O
Numpy
An introduction to one of the most fundamental packages in scientific computing
Numpy-Array-basics
Basics of Numpy’s homogenous, multidimensional arrays
Numpy-Ufuncs
Numpy universal funcs
Numpy-broadcasting-and-computation
Applying the ufuncs to multi-dimensional arrays and other generic numpy functions
Python-Matplotlib
Introduction to plotting and visualizing using python’s Matplotlib package
Matplotlib-Interactive-plotting
Plotting the plots for interactive use inside jupyter notebook
Matplotlib-types-of-plots
Introduction to some of the different types of plots in Matplotlib packages
Matplotlib-subplots-and-annotations
Plotting multiple plots in same figure and annotating them
Python-Pandas
Working with relational and labeled datasets made easy
Pandas-Series-and-Dataframe
Introduction to the two powerful workhorse datastructures of Pandas
Pandas-Exploratory-data-analysis
Example of using pandas for performing exploratory data analysis