Introduction to AI-Assisted Programming

Generative AI has revolutionised the way content is generated, including code. The use of generative AI tools can dramatically speed up the programming process and has the potential to increase the quality of code. However, care must be taken to ensure the functionality and appropriateness of any code produced by these tools. There are also considerations relating to ethics, privacy, and academic integrity that users should be aware of.

In this course you will be introduced to GitHub Copilot, which is one of the leading tools for AI-assisted programming. You will use it in authentic situations and learn how to use it as a productive partner while reviewing code, editing code and writing new code

You will learn the basics of how generative AI works and consider it in terms of ethics, academic integrity and privacy, as well as its uses and limitations. This course includes practical tips on how to best integrate the Copilot into programming practice, including suggestions of how to ask the most useful questions and how to use Copilot’s code suggestions in your development process.

Syllabus

• Introduction to generative AI
• The GitHub Copilot interface
• Reviewing code with GitHub Copilot
• Editing code with GitHub Copilot
• Writing new code with GitHub Copilot

The course will be a mixture of lecture-like materials, demonstrations, and hands-on exercises working with Copilot. The examples in the course are primarily written in Python, but knowledge of Python is not essential for the course. This course is aimed at anyone who programs, and you should be familiar with the basics of at least one programming language before attending.

This course is open to Research Degree Students, Postdocs & Fellows. Limited spaces available for wider Imperial community.

Learning outcomes

By the end of the course, you will be better able to:

• Describe the basics of how generative AI works.
• Discuss common ethical considerations around the use of generative AI in the context of programming.
• Evaluate when it is appropriate to use AI assistance when programming.
• Use a common generative AI tool to assist programming, including critically evaluating its output.
• Design prompts most likely to produce useful outputs.

Prerequisites

• You should be familiar with the basics of at least one programming language.
• Familiarity with the basics of Python (such as from the online course Introduction to Python for Researchers (Online Course) would be helpful but is not required.
• You must follow the pre-course instructions at least 10 days before the course.

How to book

• Early Career Researchers (Research Degree Students, Postdocs, Research Fellows) should book via Inkpath using your Imperial Single-Sign-On.
• All other members of the Imperial community, should book here.

Please ensure you have read and understood ECRI’s cancellation policy before booking.