Welcome to the STOR-601 Introductory Python Module#

The course#

This course is an introduction to python programming for statistics and data science. Since it is an introductory course it does not cover every aspect of the python programming system.

Initially, the course focuses on the python language. The later sessions then introduce python libraries that are particularly useful for statistics and data science.

The material is presented using jupyter notebooks and jupyter book. You can learn more about jupyter here

The approach to teaching is hands on. You are expected to try as many exercises as you can. The jupyter notebooks for the course can be downloaded and extended with your own notes, examples, and ideas.

Course contacts#

Daniel Grose - Lecturer

Sessions#

  • Session 1

    • Tuesday 09/01/2024

    • Lab 2 PSC

    • 10:00 - 12:00

  • Session 2

    • Tuesday 09/01/2024

    • Lab 2 PSC

    • 13:00 - 15:00

  • Session 3

    • Wednesday 10/01/2024

    • Lab 2 PSC

    • 10:00 - 12:00

Assessment#

  • One piece of assessed work

  • Issued in session 3 (10/01/2024)

  • Due 09:00 on 05/02/2024

  • Submitted as jupyter notebook

Approach to learning#

  • Single jupyter book for course notes

  • Course notes designed to accompany the sessions

  • Each chapter is a jupyter notebook

  • Each notebook can be downloaded and annotated by you

  • Course notes have lots of examples and exercises

Why Python ?#

  • Easy to learn

  • Versatile

  • Syntax is easy to read

  • Lots of open source libraries

  • Used for more than statistics and data science

  • Easy to integrate into larger systems

Outcomes#

Session 1 - The basics#

  • Variables and expressions

  • Functions

  • Importing libraries

  • Installing libraries

  • Lists

  • if, elif, and else

  • for, while

  • Tuples

  • Dictionaries

  • File input and output

Session 2#

  • Classes

  • numpy

  • pandas

  • matplotlib

  • statisitics with scipy

Session 3#

  • ggplot

  • libraries for data science