Course
Digicomp Code H40862
Generative AI in Software Development – with GitHub Copilot, ChatGPT, and others («H40862»)
Course facts
- Learning how AI assistants can take over coding tasks and save you a lot of time
- Learning specific techniques for integrating generative AI tools into your own workflows and those of your team—for coding, testing, refactoring, and much more
- Getting an overview of advanced features of GitHub Copilot and learning about powerful new tools such as GitHub Codespaces and Devin AI
- Expanding your horizons and learning new areas of application for AI-assisted software development
- Gaining advanced insights into how AI assistants can be customized, creating your own workflows, and integrating different AI models
- Assessing the legal implications and liability issues involved when code is generated by AI
1 Generative AI and LLMs in a nutshell
- What can generative AI do, and what will it never be able to do?
- How do LLMs work, and how do I get my files into them?
- How can artificial intelligence help in software development?
- An overview of AI assistants for all areas of application
2 Generative AI in Coding
- Writing, debugging, and documenting code with AI assistants
- Using generative AI for code analysis
- Refactoring with AI support
- Software testing with AI
3 Generative AI in software projects
- Requirements engineering with artificial intelligence
- AI as an aid in software design
- Coding styles and patterns with generative AI
- Security auditing with AI
4 Creative uses of generative AI
- Building extensions for GitHub Copilot
- Letting GitHub Copilot learn from existing code
- Using different AI models and hosting them locally
- A look into the future: the AI-driven software process
5 Other important considerations
- Security issues with AI-generated code
- Who owns the copyright to generated code?
- Who is liable for faulty or defective code?
- Privacy by design: Complying with data protection regulations
This online seminar will be held in a group of no more than 12 participants using Zoom video conferencing software.
Individual support from the instructors is guaranteed—either in the virtual classroom or individually in breakout sessions.
The practical exercises will mainly be carried out using GitHub Copilot and ChatGPT. Access to the paid versions is not essential for participation in the course, but is advantageous. The instructors will be on hand to assist you with the practical exercises.
After registering, you will find all the information, downloads, and extra services relating to this qualification measure in your online learning environment.
This training is aimed at anyone working in software development: developers, DevOps engineers, data scientists, machine learning engineers, software testers, system architects, product owners, and many more.
IT consultants, team leads, and tech leads will gain a good understanding of how AI tools can be used to support software teams.
IT project managers and service managers will learn about tools, processes, and methods that can be used to increase productivity and speed in software projects.
There are no formal requirements for participation in this course.
To ensure that you receive any necessary documents by mail in good time, we recommend booking at least 14 days before the seminar date.