Summary and Schedule

This is a new lesson built with The Carpentries Workbench.

	Setup Instructions	Download files required for the lesson
Duration: 00h 00m	1. The AI Landscape	Where does generative AI fit within the broader historical and technical landscape of AI systems? How do large language models generate text, code, or explanations without understanding meaning in a human sense?
Duration: 00h 12m	2. AI-Assisted Coding Practical Skills	How can AI be used effectively as a reference or learning aid rather than a substitute for problem-solving? What types of coding tasks benefit most from AI assistance? How should developers evaluate and validate AI-generated code, explanations, or fixes?
Duration: 00h 24m	3. Ethics, Reliability and Security Considerations	What are some risks of biased, inaccurate, or unreliable AI-generated outputs? How can the use of AI tools compromise data privacy, security, or confidentiality in research and software development? What intellectual property and authorship issues emerge when AI contributes to code or written work? What are the long-term consequences of researchers relying on AI without developing core coding skills? What best practices can ensure that AI is used responsibly, ethically, and transparently in research workflows?
Duration: 00h 36m	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

A practical introduction to using AI to support coding in research. This course will help researchers understand how to use AI to help them write code effectively and responsibly. This course is designed for researchers with little to no experience coding. The course provides clear, hands-on guidance for using AI to write, debug, and understand code, while addressing key ethical, security, and reliability considerations in research contexts.

Data Sets

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Download the dataset we will work with by clicking here: animals.csv

Save it to your desktop or another easily accessible location.

Callout

Where does the data come from?

The data we’re working with comes from the Portal Project, a long-term ecological study being conducted near Portal, Arizona. Since 1977, the site has been used to study interactions between rodents, ants and plants.

For this workshop, we use a CSV file that is a subset of the teaching-focused Portal dataset. This version has been simplified by removing some of the complexities of the full dataset, making it more suitable for computational training and learning exercises.

Software Setup

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AI Tool

You need to be able to access an AI Chat tool such as ChatGPT or Microsoft CoPilot.

Anaconda Navigator

To run the code examples used in this workshop, you will need a way to execute Python code on your computer.

The instructor will be using Jupyter Notebooks via Anaconda Navigator. Unless you already have a preferred Python setup, we recommend installing Anaconda Navigator and running the examples using Jupyter Notebooks from within it. This provides a simple, self-contained environment with all required tools pre-installed. Instructions to install Anaconda Navigator on University of Southampton computers and personal computers are in the blocks below:

University of Southampton Computers

If you are using a computer provided by the University of Southampton, please use the ‘Software Center’ icon to download Anaconda Navigator. This icon is on the desktop of all university-managed laptops, desktops and CLS workstations used by students and staff. You can install the most common software types from this shortcut.

Personal Computers

Follow these steps to install Anaconda Navigator on your personal computer. The process is similar on Windows, macOS, and Linux.

Step 1: Go to the Anaconda Website

1. Open a web browser.
2. Visit: https://www.anaconda.com/products/distribution

Step 2: Choose the Installer

1. Click Get Started.
2. Select the Anaconda Distribution installer for your operating system:
   • Windows
   • macOS
   • Linux
3. Choose the 64-bit graphical installer unless you have a specific reason to use another option.

Step 3: Download the Installer

1. The installer file will begin downloading automatically.
2. Wait for the download to complete (this may take a few minutes).

Step 4: Run the Installer

• Windows
  1. Double-click the downloaded .exe file.
  2. Click Next through the welcome screens.
  3. Accept the license agreement.
  4. Choose Just Me when prompted.
  5. Use the default installation location.
  6. Click Install.
• macOS
  1. Double-click the downloaded .pkg file.
  2. Follow the on-screen instructions.
  3. Accept the license agreement.
  4. Use the default installation settings.
  5. Click Install (you may be asked for your computer password).
• Linux
  1. Open a terminal.
  2. Navigate to the folder containing the downloaded .sh file.
  3. Run the installer: bash Anaconda3-*.sh
  4. Follow the on-screen prompts and accept the defaults.

Step 5: Launch Anaconda Navigator

1. After installation completes, open Anaconda Navigator:
   • On Windows or macOS: search for Anaconda Navigator in your applications.
   • On Linux: run anaconda-navigator from the terminal.
2. Wait for the Navigator interface to load.

Step 6: Verify Installation

1. In Anaconda Navigator, find Jupyter Notebook.
2. Click Launch.
3. If Jupyter opens in your web browser, the installation was successful.

If Anaconda Navigator does not open or you encounter issues, restarting your computer often resolves initial setup problems.