Introduction to Numpy and SciPy
NumPy (Numeric Python) and SciPy (Scientific Python) are add-on modules to Python that provide common mathematical and numerical routines in pre-compiled, fast functions. NumPy supplies basic routines for manipulating large arrays and matrices of numeric data. Numpy is the most basic and a powerful package for working with data in Python. SciPy extends the functionality of NumPy with a substantial collection of useful algorithms such as minimization, Fourier transformation, regression, and other applied mathematical techniques.
We introduce NumPy and SciPy to allow participants to get familiar with some broad functionalities of the two modules and their use in real applications.
| Lecture Topic | Interactive Link | Lecturer |
|---|---|---|
| Introduction to Numpy |  |
Jules |
| Introduction to SciPy | |
Jules |
| Feedback Session | Survey on Numpy |
In case you want to obtained the materials using git commands:
git clone https://github.com/pytrain/numpy.git
git clone https://github.com/pytrain/scipy.git