Introduction to Python

This site gives details on how to access the Introduction to Python material that has been designed for students planning to study the University of Sheffield's Data Analytics MSc. The material is designed for you to work through in your own time before you start with us in Sheffield.

The material is divided into two parts:

• Part 1 (Introduction to Python) covers the Python programming language and introductory programming concepts.
• Part 2 (Python for Data Analytics) covers more advanced material about the numpy package for scientific computing.

You should attempt to complete all of the exercises in Part 1. We also advise that you attempt the exercises in Part 2, they provide information that will be very useful for your course, but they may prove to be too complicated at this stage. If that's the case then you can revisit them later.

Jupyter Notebooks

The course materials are delivered as Jupyter Notebooks which is a literate computing platform that is widely used in data science. The Jupyter Notebooks are available on a GitHub repository (https://github.com/SheffieldDataAnalytics/Python-for-Data-Analytics) but cannot be run there directly. We recommend that you run them on a cloud-based environment so that only a standard web browser is required and you do not have to install any software on your own computer. Instructions for one such service (Google Colab) are provided. Alternative services are also available (see below).

• Google Colab allows Jupyter notebooks to be run via Google Drive for free. A Google account is required for access. It is recommended that you use Colab by following these simple steps.
• CoCalc provides a similar interface to Notebooks_ and offers a free plan.