Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lesson covers, the difference between qualitative and quantitative data the difference between discrete and continuous data. Lesson content, A PowerPoint/PDF presentation, ‘Qualitative & Quantitative’ Excel/PDF Question workbook on ‘Qualitative & Quantitative’ (for learners) Excel/PDF Answers workbook on ‘Qualitative & Quantitative’ (for teachers) Planning document with learning intentions and sucess 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. © 2021. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lesson follows on from ‘The Analysis Process’ which is available from the effini TES shop. This lesson covers the data understanding part of the analysis process in Excel, specifically, • what is metadata and the importance of a data dictionary • how to identify the shape and size of a dataset in Excel and data types of variables • how to identify missing values and outliers in Excel Lesson content, A PowerPoint/PDF presentation, ‘Dataset understanding in Excel’ Excel Question workbook on ‘Dataset understanding in Excel’ (for learners) Excel/PDF Answers workbook on ‘Dataset understanding in Excel’ (for teachers) 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. © 2022. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Level 5 and 6. This lessons follows on from the ‘Practise combining datasets’ lesson which is available from the effini shop. This lesson covers how to combine datasets in Excel, specifically: how to join datasets when the key columns have different names how to join datasets with multiple key columns how to solve problems by selecting the appropriate join type Lesson content: • A lesson plan (this document) • a PowerPoint presentation, ‘Advanced practise combining datasets in Excel’ • a question worksheet (for learners) on ‘Advanced practise combining datasets in Excel’ in Excel • an answers worksheet (for teachers) on ‘Advanced practise combining datasets in Excel’ in Excel a planning document with learning intentions and success criteria For more information on the Data Science NPA, please see teachdata.science. If you have any questions or feedback please email lessons@effini.com This lesson has been created by effini in partnership with The Data Lab. © 2024 This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lesson covers how to summarise datasets in Python (part 2 of 2), specifically, group rows of data based on logical criteria perform summary calculations on grouped data Lesson content, A PowerPoint/PDF presentation, ‘Summarising datasets in Python (part 2)’ Jupyter notebooks: ‘summarising_datasets_with_answers_part_2.ipynb’ (for teachers) ‘summarising_datasets_part_2.ipynb’ (for learners) Datasets used in the Jupyter notebooks: the datasets are stored online and imported by the Jupyter notebooks. 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. © 2021. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lessons covers how to creating bar charts and histograms in Excel, specifically, • how to amend the font, colour and display format of graph elements • how to amend gridlines on a graph • how to change the order and gaps of the bars in a bar chart • how to change the size of the bins in a histogram Lesson content, A PowerPoint/PDF presentation, ‘Practise creating graphs in Excel (part 1)’ Excel Question workbook on ‘Practise creating graphs in Excel (part 1)’ (for learners) Excel Answers workbook on ‘Practise creating graphs in Excel (part 1)’ (for teachers) Planning document with learning intentions and success criteria For more information on the Data Science NPA, please see teachdata.science If you have any questions or feedback on this lesson, please email lessons@effini.com 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. © 2022. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Level 6. This lesson covers how to use data ethically, specifically, What is bias and the causes of bias How to mitigate against data bias. Lesson content, A PowerPoint/PDF presentation, ‘Causes & impacts of bias’ Excel Question workbook on ‘Causes & impacts of bias’ (for learners) Excel Answers workbook on ‘Causes & impacts of bias’ (for teachers) Planning document with learning intentions and success criteria For more information on the Data Science NPA, please see teachdata.science If you have any questions or feedback please email lessons@effini.com This lesson has been created by effini in partnership with Data Education in Schools and Skills Development Scotland. © 2022 This work is licensed under a CC BY-NC-SA 4.0 license.

This document is a guide to the educational resources developed by effini, in collaboration with Data Education in Schools and The Data Lab, to support educators delivering the National Progression Award (NPA) in Data Science or Professional Development Award (PDA) in Data Science. It provides an overview of these resources and is intended to be used by educators. It provides educators with information on: • What the NPA and PDA in Data Science are • Options for delivering the NPA • What the resources are • What can be done with them, and • How to access them. If you have any questions, please contact us at lessons@effini.com

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lesson covers what is involved in the analysis process, specifically, • what we mean by analysis • a structured way of performing analysis (the analysis steps) • how to understand data through visual inspection Lesson content, A PowerPoint/PDF presentation, ‘The analysis process’ Excel Question workbook on ‘The analysis process’ (for learners) Excel Answers workbook on ‘The analysis process’ (for teachers) 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. © 2021. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Level 5 and 6. This lessons follows on from the ‘Combining datasets’ lesson which is available from the effini shop. This lesson covers how to combine datasets in Python, specifically, • how to append rows to a dataset, and • how to join columns to a dataset Lesson content, A Powerpoint presentation, ‘Practise Combining Datasets in Python’ Jupyter notebooks: o ‘practise_combining_datasets_with_answers.ipynb’ (for teachers), and o ‘practise_combining_datasets.ipynb’ (for learners) Datasets used in the Jupyter notebooks: the datasets are stored online and imported by the Jupyter notebooks. Planning document with learning intentions and success criteria For more information on the Data Science NPA, please see teachdata.science If you have any questions or feedback please email lessons@effini.com This lesson has been created by effini in partnership with The Data Lab. © 2023 This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Level 5 and 6. This lesson follows on from ‘Combining datasets’ lesson, which is available from the effini TES shop. This lesson covers how to combine datasets in Excel, specifically, • how to use Power Query Editor to append rows to a dataset • how to use Power Query Editor to join columns to a dataset Lesson content, A PowerPoint/PDF presentation, ‘Practise combining datasets in Excel’ Excel Question workbook on ‘Practise combining datasets in Excel’ (for learners) Excel Answers workbook on ‘Practise combining datasets in Excel’ (for teachers) Planning document with learning intentions and success criteria For more information on the Data Science NPA, please see teachdata.science If you have any questions or feedback please email lessons@effini.com This lesson has been created by effini in partnership with The Data Lab. © 2023 This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 5 and 6. This lesson follows on from ‘Dataset cleansing in Python’ (part 1 & 2) and ‘Advanced data cleansing in Python’ (part 1 & 2) which are available from the effini TES shop. This lesson allows learners to practise the skills covered in the Data Cleansing part of the analysis process in Python, specifically, • how to rename variables • how to drop unrequired rows and variables • how to drop duplicates • how to handle missing data and outliers Lesson content, A PowerPoint/PDF presentation, ‘Practise data cleansing in Python’ 2 Jupyter notebooks: ‘practise_data_cleansing.ipynb’ (for learners) ‘practise_data_cleansing_with_answers.ipynb’ (for teachers) 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. © 2022. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lessons covers how to create graphs in Excel, specifically, how creating graphs fits into the analysis steps process of creating bar charts and histograms process of creating line graphs and scatterplots Lesson content, A PowerPoint/PDF presentation, ‘Creating graphs in Excel’ Excel Question workbook on ‘Creating graphs in Excel’ (for learners) Excel Answers workbook on ‘Creating graphs in Excel’’ (for teachers) Planning document with learning intentions and success criteria For more information on the Data Science NPA, please see teachdata.science If you have any questions or feedback on this lesson, please email lessons@effini.com 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. © 2021. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 5 and 6. This lesson follows on from ‘The Analysis Process’ and the ‘Dataset cleansing in Python’ (part 1 & 2) which are available from the effini TES shop. This lesson covers the advanced data cleansing part of the analysis process in Python (part 2 of 2), specifically, • how to fix strings, • how to handle missing/outlying values Lesson content, A PowerPoint/PDF presentation, ‘Advanced data cleansing in Python (part 2)’ 2 Jupyter notebooks: ‘advanced_data_cleansing_part_2.ipynb’ (for learners) ‘advanced_data_cleansing_with_answers_part_2.ipynb’ (for teachers) 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. © 2022. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lesson follows on from ‘Dataset understanding in Excel’ lesson which is available from the effini TES shop. This lesson allows learners to practice the skills covered in the Dataset Understanding in Excel, specifically, • Using data dictionaries/metadata • Identifying size and shape • Identifying missing values and outliers Lesson content, A PowerPoint/PDF presentation, ‘Practise Dataset Understanding in Excel’ Question worksheet (for learners) on ‘Practise Dataset understanding in Excel’ in Excel Answers worksheet (for teachers) on ‘Practise Dataset understanding in Excel’ in Excel 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. © 2022. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4, 5 and 6. This lesson follows on from ‘The Analysis Process’ and the ‘Dataset cleansing in Python’ (part 1 & 2) which are available from the effini TES shop. This lesson covers the advanced data cleansing part of the analysis process in Python (part 1 of 2), specifically, • how to convert between data types Lesson content, A PowerPoint/PDF presentation, ‘Advanced data cleansing in Python (part 1)’ 2 Jupyter notebooks: ‘advanced_data_cleansing_part_1.ipynb’ (for learners) ‘advanced_data_cleansing_with_answers_part_1.ipynb’ (for teachers) 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. © 2022. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lessons is an Intro to Python for Data Science (part 2 of 2) ,covering, understand Python data types and data structures that are important for data science manipulate strings create and call Python functions call a Python object’s methods and access its properties perform a sequence of operations using method chaining Lesson content, Powerpoint presentation: ‘Introduction to Python for Data Science (Part 2)’ Jupyter notebooks: ‘intro_to_python_for_data_science_part_2.ipynb’ (for learners) ‘intro_to_python_for_data_science_with_answers_part_2.ipynb’ (for teachers) The Jupyter notebook for teachers contains answers to the tasks set for learners. Planning document with learning intentions and success criteria For more information on the Data Science NPA, please see teachdata.science If you have any questions or feedback on this lesson, please email lessons@effini.com 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. © 2021. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lessons is an Intro to Python for Data Science (part 1 of 2) ,covering, why Python is widely used in data science install, import and use Python packages understand how to get help when using Python name variables clearly and consistently Lesson content, Powerpoint presentation, ‘Introduction to Python for Data Science (Part 1)’ Jupyter notebooks: ‘intro_to_python_for_data_science_part_1.ipynb’ (for learners) ‘intro_to_python_for_data_science_with_answers_part_1.ipynb’ (for teachers) The Jupyter notebook for teachers contains answers to the tasks set for learners. Planning document with learning intentions and success criteria For more information on the Data Science NPA, please see teachdata.science If you have any questions or feedback on this lesson, please email lessons@effini.com 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. © 2021. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lesson covers, Different structures for holding data. Difference between stored and display formats Lesson content, A PowerPoint/PDF presentation, ‘Data types and storage’ Excel/PDF Question workbook on ‘Data types and storage’ (for learners) Excel/PDF Answers workbook on ‘Data types and storage’ (for teachers) Planning document with learning intentions and sucess 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. © 2021. This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Levels 4,5 and 6. This lesson covers how data can be misused, specifically, What is data misuse Malicious data misuse and how it can happen Accidental data misuse and how it can happen Lesson content, A PowerPoint/PDF presentation, ‘Data misuse’ Excel Question workbook on ‘Data misuse’ (for learners) Excel Answers workbook on ‘Data misuse’ (for teachers) Planning document with learning intentions and sucess criteria For more information on the Data Science NPA, please see teachdata.science If you have any questions or feedback please email lessons@effini.com This lesson has been created by effini in partnership with Data Education in Schools and Skills Development Scotland. © 2022 This work is licensed under a CC BY-NC-SA 4.0 license.

Free lesson resources for teaching Data Science NPA (National Progress Award) Level 6. This lesson covers how to use data ethically, specifically, What are ethical data risks How to identify ethical risks What are data ethics frameworks and how they can be used to prevent ethical risks Lesson content, A PowerPoint/PDF presentation, ‘Ethical use of data’ Excel Question workbook on ‘Ethical use of data’ (for learners) Excel Answers workbook on ‘Ethical use of data’ (for teachers) Planning document with learning intentions and success criteria For more information on the Data Science NPA, please see teachdata.science If you have any questions or feedback please email lessons@effini.com This lesson has been created by effini in partnership with Data Education in Schools and Skills Development Scotland. © 2022 This work is licensed under a CC BY-NC-SA 4.0 license.