This is my exemplar title

This is a brief abstract of my exemplar, which includes a representative image.

This exemplar was developed at Imperial College London by (YOUR NAME) in collaboration with (RSE MENTOR) from Research Software Engineering and (RCDS MENTOR) from Research Computing & Data Science at the Early Career Researcher Institute.

Learning Outcomes 🎓

After completing this exemplar, students will:

• Learning Outcome 1
• Learning Outcome 2
• Learning Outcome 3

Target Audience 🎯

Who will benefit from studying this exemplar.

Prerequisites ✅

Academic 📚

• Required skills/knowledge (e.g. programming languages, libraries, theory, courses)

System 💻

• System requirements (e.g. Python 3.11+, Anaconda, 50 GB disk space, etc.)
• Hardware or HPC requirements (if any)

Getting Started 🚀

e.g. Step-by-step guide:

1. Start by (instruction).
2. Visit the sections of this notebook in some particular order.
3. Attempt exercises 1a, 1b, etc.
4. Progress to advanced materials in the Github repository linked here.
5. Compare with solutions available in the solutions folder.

Disciplinary Background 🔬

Briefly describe how this project fits in your discipline, why you chose to work on it, and what other disciplines may find it useful.

Software Tools 🛠️

Programming language(s), libraries, and scientific software used.

Project Structure 🗂️

Overview of code organisation and structure.

.
├── notebooks
│ ├── ex1.ipynb
├── src
│ ├── file1.py
│ ├── file2.cpp
│ ├── ...
│ └── data
├── docs
└── test

Code is organised into logical components:

• notebooks for tutorials and exercises
• src for core code, potentially divided into further modules
• data within src for datasets
• docs for documentation
• test for testing scripts

Roadmap 🗺️

Core 🧩

• Data ingestion pipeline
  • Tutorial with small data exercise
• Core analysis algorithms
  • Documentation with worked example
• Basic visualisation tools
  • Mini-project: "Create your first plot"
• Results export functionality
  • Usage tutorial with export task
  • Short video walkthrough (planned)
• Automated testing suite
  • Debugging challenge
• Documentation for core methods

Extensions 🔌

• Advanced statistical models
  • Example notebook with exercises
• Interactive dashboard
  • Exercise: Build a simple component
• Multi-format data import/export
  • Guide with hands-on tasks
• Collaboration tools integration
  • Exercise: Set up collaborative workflow
  • Include diagram of workflow (optional)
• Extended visualisation options
  • Creative task: Design a custom plot

Data 📊

List datasets used with:

• Licensing info
• Where they are included (in the repo or external links)

Best Practice Notes 📝

• Code testing and/or test examples
• Use of continuous integration (if any)
• Any other software development best practices

Estimated Time ⏳

Task	Time
Reading	3 hours
Practising	3 hours

Additional Resources 🔗

• Relevant sources, websites, images, AOB.

Licence 📄

This project is licensed under the BSD-3-Clause license.