Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6.

This lesson follows on from 鈥楧ataset understanding in Python鈥� (parts 1 &2) lessons which is available from the effini TES shop.

This lesson allows learners to practise the skills covered in the Dataset understanding in Python lessons, specfically,
鈥� how to import a dataset without importing metadata
鈥� how to use a data dictionary to find out about a dataset
鈥� how to find the shape, size and format of datasets, using Python
鈥� how to find the data types of variables in a dataset, using Python
鈥� how to identify outliers and missing values in Python

Lesson content,

A PowerPoint/PDF presentation, 鈥楶ractise Dataset Understanding in Python鈥�
Jupyter notebooks:

• 鈥榩ractise_data_understanding withanswers.ipynb鈥� (for teachers), and
• 'practise_data_understanding.ipynb鈥� (for learners)
  Datasets used in the Jupyter notebook: the datasets are stored online and imported by the Jupyter notebook.
  Planning document with learning intentions and success criteria
  For more information on the Data Science NPA, please see teachdata.science

This lesson has been created by effini in partnership with Data Education in Schools, The Data Lab and Data Skills for Work, with funding from the Scottish Government.

漏 2022. This work is licensed under a CC BY-NC-SA 4.0 license.