Course overview
This expert-level course deepens and further advances the skills in the intermediate-level course. It is taught using a multidisciplinary approach and focuses on providing learners with the knowledge necessary to apply ethical AI principles in practical settings. It uses real-world case studies, self-reflection worksheets, hands-on coding exercises and thought experiments to give the learner the tools to continue learning after the course is completed.
This course has been commissioned as part of our open funding call for Responsible AI courses, with funding from Accenture and the Alan Turing Institute.
Who is this course for?
The course is accessible for businesses, organisations or people developing, evaluating, or distributing AI.
The course requires a:
- Basic understanding of artificial intelligence
- Basic understanding of existing regulatory landscape
- Basic understanding of programming in python (for example, Jupyter)
Learning outcomes
By the end of this course you will be able to:
- Critically reflect on ethical concepts and to select and apply relevant one
- Obtain a basic understanding of the value and role of transparency and fairness within different domains of applications
- Identify relevant concepts of fairness and transparency to the domain of application
- Evaluate and apply relevant algorithmic techniques and tools
- Carry out a technical breakdown of model performance that assesses transparency and fairness
- Apply gained knowledge of socio-technological concepts to use cases.
License
This course is released under a CC BY 4.0 license.
Materials can also be found on GitHub.
