This lesson is in the early stages of development (Alpha version)

Introduction to Python - theory sessions

This is a condensed introduction to Python and Spyder. We have aimed to provide you with the basic information you need to tackle statistics and machine learning. It is a big task to learn a programming language especially if you have no experience. You will not be fluent in Python by the end of this session, but hopefully you will be off to a good start.

By the end of this workshop, students will know how to:

Prerequisites

  • Participants need to have complete pre-worksheet to ensure all the software and packages needed for this course are installed.
  • Participants understanding file management on their operating system.

Schedule

Setup Download files required for the lesson
00:00 1. Spyder Layout, navigating the IDE, project setup How is Spyder laid out?
How do we create a project and why is it important?
00:05 2. Seeking help Where can I find help?
00:10 3. Calculating in Spyder How do we process mathematical operations in Spyder?
00:20 4. Variables and assignment What can we store in variables?
What is good practice for variable naming?
What can I do with variables?
00:40 5. Arrays and vectorisation with NumPy How do we manage many variables efficiently?
01:00 6. Lists and dictionaries in Python What other data structures are there?
01:20 7. Flow control How do we get our code to react dynamically?
How do we delegate repetitive tasks and decisions?
How do we make our software robust to a wider set of use cases?
01:50 8. Functions How do I make my own functions?
Why would I want to make my own functions?
02:10 9. Loading data into Python using Spyder How do I load my own data into Spyder?
02:20 10. Pandas and manipulating data frames How do I manage tabular data efficiently?
02:50 11. Plotting in Python with Matplotlib How do I create plots?
How do I use data sets to populate my plot?
03:05 12. Practical session Can you apply the theory to some practical problems?
05:15 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.