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  1. Session Schedule
  • Session Schedule
  • Onboarding
    • 1. Python Onboarding
    • 2. Jupyter Notebooks
  • Exploration & Visualisation
    • 3. EDA with Pandas
    • 4. Visualisations with Seaborn
    • 5. EDA with Seaborn
  • Core Concepts
    • 6. Data Types
    • 7. Control Flow
    • 8. Functions & Functional Programming
    • 9. Object-Oriented Programming
  • Exploration & Visualisation
    • 10. Streamlit Dashboards
  • Data Science
    • 11. Comparing Samples
    • 12. Analysing Relationships
    • 13. Introduction to Linear Regression
    • 14. Implementing Linear Regression
    • 15. Beyond Linearity

Schedule

This is the schedule for Code Club in FY25/26.

The Demonstration, Presentation, and Notebook columns indicate the content to be expected for each session:

  • Demonstration: A live show-and-tell relating to the discussion topic.
  • Presentation: A slide deck covering the discussion topic.
  • Notebook: A Jupyter Notebook containing code-along elements or examples for people to work through after the session.

Tutorials will be divided into Modules. We recommend that people attend or watch tutorials in the Core module in order to gain a fundamental understanding of coding concepts and resources. Further modules are to be confirmed, but will likely include Automation, Dashboards and Visualisation, and Data Science. People will be able to attend those modules that interest them.

We have mapped the contents of the syllabus to competencies in the National Competency Framework for Data Professionals in Health and Care so that you can see which sessions will help you on your way towards them. For full details of the skills in the framework, the self-assessment tool can be found on FutureNHS.

Please note that this is a first draft of the mapping of NCF competencies to our syllabus and it is awaiting review.

Session Date Module Session Name Description Demonstration Presentation Notebook NCF Competency
22/04/2025 N/A Nectar Re-Launch Showcasing the re-launch of Code Club 🎬 💻 - -
01/05/2025 On-boarding Python On-boarding What to install, basic virtual environment management, introduction to VS Code 🎬 - - SA21 : Python Proficiency
15/05/2025 On-boarding Jupyter Notebooks Demonstration of Jupyter Notebooks 🎬 - 📖 SA21 : Python Proficiency
29/05/2025 Exploration & Visualisation EDA with Pandas Introduction to exploratory data analysis using pandas 🎬 - 📖 SA4 : Descriptive and Explicative Analytics
12/06/2025 Exploration & Visualisation Visualisation with Seaborn Aesthetically-pleasing visualisations 🎬 - 📖 SA1 : Data Visualisation
03/07/2025 Exploration & Visualisation EDA with Seaborn Using seaborn to visualise and explore data 🎬 - 📖 SA4 : Descriptive and Explicative Analytics
17/07/2025 Core concepts Data Types Introduction to data types - 💻 📖 SA21 : Python Proficiency
31/07/2025 Core concepts Control Flow Introduction to control flow - 💻 📖 SA21 : Python Proficiency
14/08/2025 Core concepts Functions & Functional Programming Introduction to functions and functional programming - 💻 📖 SA21 : Python Proficiency
28/08/2025 Core concepts Object-Oriented Programming Introduction to object-oriented programming - 💻 📖 SA21 : Python Proficiency
11/09/2025 Exploration & Visualisation Streamlit dashboards How to present data (visualisations) in a Streamlit dashboard 🎬 - - SA1 : Data Visualisation
25/09/2025 Data Science Comparing Samples Understanding data distributions and comparisons between samples - 💻 📖 SA4 : Descriptive and Explicative Analytics
09/10/2025 Data Science Analysing Relationships Quantifying relationships with hypothesis tests and statistical significance - 💻 📖 SA15 : Hypothesis Testing
23/10/2025 Data Science Introduction to Linear Regression Introduction to regression concepts and the component parts of linear regression - 💻 📖 SA7 : Advanced Statistics
06/11/2025 Data Science Implementing Linear Regression Building linear models, assessing model fit, and interpreting coefficients 🎬 💻 📖 SA7 : Advanced Statistics
20/11/2025 Data Science Beyond Linearity Introduction to generalised linear regression models 🎬 💻 📖 SA7 : Advanced Statistics

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