__Welcome to the STOR-601 Introductory Python Module__

## Contents

__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