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Python Course README

This is the content of a set of Python courses. For more details see the course outlines

Foundation course - agenda

Getting started lesson and exercise

Data types lesson and exercise

Control flow lesson and exercise

Strings (and methods, and indexing / slicing) lesson and exercise

Data Structures

List comprehensions lesson and exercise

We may need to install a package.

Using the requests package

A very brief look at some common modules and packages: datetime; math and statistics

Intermediate course - agenda

Consolidation of foundation content day2_starter_exercise. This revises strings, lists, conditional flow, and has a final brain teaser exercise

Writing functions lesson, exercise and another exercise

Practical Examples

OpenAI demo connects to ChatGPT to have a conversation

Web Scraping tutorial

Read and write Excel files: a simple starter example and a more complete example that reads several tables from an Excel file into pandas DataFrames, merges the the tables, summarises the data, creates a chart then exports the summarised data in both CSV and Excel file formats

Introduction to data analysis with pandas - tutorial

Introduction to data visualisation with seaborn - tutorial

Retrieving data from SQL - demo

Retrieve Data from an API / web pages the requests package

Advanced course - agenda

The advanced course focusses on data analysis with the numpy, pandas and seaborn packages. The numpy package underpins many data analysis packages (including pandas), and AI packages.

numpy lesson and exercise

pandas is the library for data analysis in Python. The course covers it in detail.

Visualise data with the seaborn package.

Functional and object-oriented styles of programming

Functional programming lesson and exercise

Building classes (object-oriented programming) lesson and exercise

Optional sections

If time allows, a very brief look at:

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