This two-day course is an introduction to Python programming and Jupyter Notebooks, beginning with the most basic operations of downloading and installing the Python environment. The course will use Anaconda, a popular Python distribution for data science that includes many of the packages used in this course.
The course will also introduce core Python objects and operations, Numpy for statistical and matrix operations, matplotlib and Plotly for visualisations, and Pandas, a comprehensive data manipulation and analysis package.
Participants will learn how to input, read, write, and manipulate data, primarily using Pandas, and be instructed in all the aspects of procedural programming in Python, allowing them to create their own Python modules.
Jupyter Notebooks will be featured as the recommended interface to write code, explore and analyse data, and to document and communicate the results of the data analysis with interactive visualisations.
The course is focused on providing a foundation for participants to use Python for exploratory data analysis and visualisation, which can be used as a stepping stone to machine learning using the popular scikit-learn package and deep-learning packages unique to Python. Familiarity with Python will allow users to use packages and access data and web services that have existing connections to Python, e.g. natural language processing, APIs, and web scraping.
The course will make use of the Anaconda Distribution of Python and some of the training may be demonstrated using Microsoft Azure Notebooks or on the Microsoft Data Science Virtual Machine.