Programming language Python - practical usage of IPython Notebook, libraries Numpy and Matplotlib

Python is an interpreted high-level programming language that currently ranks among the most popular programming languages overall. It is a so-called multiparadigm language, which means it supports various programming paradigms including object-oriented, imperative, procedural, or functional. Although Python is often referred to as a scripting language, its capabilities are much broader. Currently, Python is massively used for numerical computations, data analysis, statistical computations, graph work, etc. This course focuses specifically on the area of numerical computations and graph work.

Target Audience

• Users with basic programming knowledge who want to start using this modern programming language in the field of numerical computations, vector and matrix operations, signal processing, statistics, and graph creation.

Course Objectives

• To acquaint participants with the practical use of the commonly used trio of technologies: Jupyter Notebook, the Numpy library, and also the Matplotlib library.

Course Outline:

Jupyter Notebook

• Basic information about Jupyter Notebook
• Installation and running of Jupyter Notebook

Numpy Library

• Basics upon which the Numpy library is built
• Data types of elements making up arrays
• Array constructors
• Casting all elements in an array
• Changing array shapes
• Indexing array elements with content from another array
• Creating "slices" from arrays
• Arrays and relational operators, selecting array elements based on a specified condition
• Mathematical functions applicable to array elements
• Matrix addition, subtraction, and multiplication
• Calculating the determinant and the inverse of a matrix
• Solving systems of linear equations

Graph plotting using NumPy and Matplotlib libraries

• Adding labels to graphs
• Polar graph Simple bar graph and graph with two groups of bars
• Displaying a histogram
• Pie chart
• Bar graph with error bars
• Contour plot

Additional Topics

• Mention of other related technologies, especially the SciPy library

Participant Prerequisites

• Programming knowledge, sufficient at a basic level (ideally knowledge of Python, C, or Java)
• Ability to work in a command line interface

Additional Requirements

• Computer with any operating system, ideally Linux (not a requirement)
• Web browser
• Terminal (console)