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‎README.md‎

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<img src="./images/UCAM_ICCS_Logo.png" width="600">
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# Reproducibility in Computing
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This repository contains documentation, resources, and code for the `<your course title>` session
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designed and delivered by Jack Franklin and Marion Weinzierl of [ICCS](https://github.com/Cambridge-ICCS).
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All materials, including slides and videos, are available such that individuals can cover the
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course in their own time.
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A website for this workshop can be found at [\<Link to website or slides if available\>](https://iccs.cam.ac.uk/).
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## Contents
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- [Learning Objectives](#learning-objectives)
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- [Teaching material](#teaching-material)
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- [Preparation and prerequisites](#preparation-and-prerequisites)
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- [Installation and setup](#installation-and-setup)
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- [License information](#license)
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- [Contribution Guidelines and Support](#contribution-guidelines-and-support)
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## Learning Objectives
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The key learning objective from this workshop is to
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_Provide participants with \<Your workshop objective here\>_.
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However, more specifically we will achieve this through to:
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* add more detailed objectives here,
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* list any specific tools and techniques to be used,
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* add any other sub-skills that will be covered,
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* state what the outcome of the exercises/lecture will be.
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With regards to specific content we cover:
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* optionally, consider adding specific takeaway skills here
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* for example, classification and regression with neural networks
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* for example, how to add and commit files to git
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## Teaching Material
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### Slides
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The slides for this workshop can be viewed here: [\<Link to your slides\>](https://iccs.cam.ac.uk/)
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### Exercises
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The exercises for the course can be found in the [exercises](exercises/) directory.
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These take the form of \<partially completed jupyter notebooks/downloadable code/online tasks or games etc.\>.
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### Worked Solutions
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Worked solutions for all of the exercises can be found in the [worked solutions](worked-solutions/) directory.
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These are for recapping after the course in case you missed anything, and contain example solutions.
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## Preparation and prerequisites
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### Prerequisites
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To get the most out of the session we assume a basic understanding in a few areas and
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for you to do some preparation in advance.
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This expected knowledge is outlined below, along with resources for reading if you
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are unfamiliar with any areas.
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- List here any key skills or knowledge that will be assumed of a user for the course,
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- for example, basic calculus (integration and differentiation of a function) and matrix algebra
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- Provide resources where appropriate,
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- for example, Basic Neural Networks - we recommend the
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[video series by 3Blue1Brown](https://www.3blue1brown.com/topics/neural-networks), at least chapters 1-3.
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- Also include any programming expectations
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- for example, the course will be taught in Python using [`numpy`](https://numpy.org/)
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and [`pandas`](https://pandas.pydata.org/docs/getting_started/index.html).
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- We assume users are familiar with the basics of Python. This includes:
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- Basic mathematical operations
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- Writing and running scripts/programs
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- Writing and using functions
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- If users need to clone the repository from GitHub/Lab using git also note this.
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The [ICCS Summer School](https://www.youtube.com/watch?v=ZrwzK4CnJ3Q) should provide the necessary knowledge.
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### Preparation
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List here anything that you expect participants to have on their computer in advance of the course in order to participate.
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For example:
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- A text editor - e.g. vim/[neovim](https://neovim.io/), [gedit](https://gedit.en.softonic.com/), [vscode](https://code.visualstudio.com/), [sublimetext](https://www.sublimetext.com/) etc. to open and edit code files
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- A terminal emulator - e.g. [GNOME Terminal](https://help.gnome.org/users/gnome-terminal/stable/), [wezterm](https://wezfurlong.org/wezterm/index.html), [Windows Terminal (windows only)](https://learn.microsoft.com/en-us/windows/terminal/), [iTerm (mac only)](https://iterm2.com/)
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- A Python 3 installation
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Remember that participants will have a mix of Unix and Windows systems, and these should be covered
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to ensure smooth delivery. Whilst Unix may be a presumed first choice, provide links to information
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for setup on Windows, for example
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[Windows' getting-started with python information](https://learn.microsoft.com/en-us/windows/python/beginners).
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If you require assistance or further information with any of these please reach out to
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us before the session.
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## Installation and setup
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Here you should include any instructions required for setup in preparation for the course.
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These may be followed during the sesison as a walkthrough, but you should provide clear
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instructions here for participants who take longer, needs additional help, or return to work
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in their own time.
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It is possible that many participants will not have done this in advance,
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which you should be prepared for, but having these clear instructions means
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that they can be pointed at this instead of holding up the session.
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Things to include are:
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- obtaining the code, for example instructions on how to clone the code locally:
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```
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git clone https://github.com/Cambridge-ICCS/<your-repository>.git
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```
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or fork the repository if this is required.
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- Setup of a computing environment if appropriate.
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e.g. in Python:
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```
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python3 -m venv my-workshop-venv
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source my-workshop-venv/bin/activate
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deactivate
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```
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- Installation of any dependencies
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- Provide links and instructions
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- If using Python, Julia, R etc. package these or use a `requirements.txt` file
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- getting started instructions
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- instructions on how to get started with the first exercises of the workshop.
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for example, loading the first jupyter notebook, or building andnrunning the first exercise
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Note that you might consider providing a [Google Colab](https://colab.research.google.com/)
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or binder implementation that can be run online in case participants have issues using the
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code on their local machine. Instructions for this approach should also be provided.
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## License
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The code materials in this project are licensed under the [MIT License](LICENSE).
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## Contribution Guidelines and Support
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If you spot an issue with the materials please let us know by
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[opening an issue](https://github.com/Cambridge-ICCS/<your-repository>/issues)
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here on GitHub clearly describing the problem.
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If you are able to fix an issue that you spot, or an
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[existing open issue](https://github.com/Cambridge-ICCS/<your-repository>/issues)
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please get in touch by commenting on the issue thread.
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Contributions from the community are welcome.
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To contribute back to the repository please first
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[fork it](https://github.com/Cambridge-ICCS/<your-repository>/fork),
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make the necessary changes to fix the problem, and then open a pull request back to
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this repository clearly describing the changes you have made.
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We will then preform a review and merge once ready.
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If you would like support using these materials, adapting them to your needs, or
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delivering them please get in touch either via GitHub or via
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[ICCS](https://github.com/Cambridge-ICCS).

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