Session Plan

Day 1

Python fundamentals and data gathering 

• Morning 

An introduction to the Jupyter IDE and fundamental types in Python. Students will learn how to:

1. Write clear, well-documented Python code in Google Colab.

2. Perform calculations using the math library.

3. Extract information from deeply nested lists and dictionaries.

• Afternoon

How to obtain data from the web. Students will learn:

1. What an API is, and the increasingly broad range of APIs available.

2. How to start using an unfamiliar API by reading and understanding the documentation.

3. How to use the requests and pandas libraries to obtain and explore data from APIs.

4. Exercises will include: obtaining live share prices from the Alphavantage API, and covid statistics from the Johns Hopkins API.

Day 2

Data exploration and visualisation

• Morning

How to explore and analyse large, complex datasets with the pandas library. Students will learn: 

1. To work with and manipulate DataFrames.

2. How to clean and check the quality of datasets.

3. To compute descriptive statistics, including correlation coefficients.

4. Exercises will include: Exploring gender pay gap data and crime data.

• Afternoon 

How to produce charts and visualizations to aid data exploration. Students will learn:

1. How to produce and interpret static charts using matplotlib and seaborn.

2. How to make interactive charts and dashboards using plotly.

3. Exercises will include: Determining the strongest predictors of house prices. 

Day 3

Working with unstructured data 

• Morning

The basics of natural language processing. Students will learn:

1. How to clean unstructured text data using the nltk library and techniques including tokenization, stopword removal, stemming and lemmatization 

2. Exercises will include analysing British political speeches 

• Afternoon 

1. Questions and troubleshooting. A chance for students to ask for advice on project work, get help with debugging their code, or ask any other burning Python questions.