Gain the technical tools to ensure that your AI systems are unbiased, i.e., their decision-making process is ethical and fair against all potential societal groups.
This course helps reinforce the importance of identifying various sources of bias and understanding what impact these can have on the development and deployment of AI systems We aim to give you knowledge of the different contexts in which bias concerns can arise, by providing examples of bias concerns and give possible strategies for how to detect (and possibly address) such issues.
On-demand - training that’s even more flexible
BSI’s on-demand courses are market-leading and available 24/7. Developed by top subject matter experts, they contain the same high-quality content you will find in our tutor-led training, but with the added benefit of being able to learn at your own pace and at any time.
How will I benefit?
This course will help learners to:
- Build a toolset of methods that can help identifying bias and fairness issues
- Identify potential sources of unwanted bias and terms to specify the nature of potential bias
- Assessing bias and fairness through metrics
- Addressing unwanted bias through treatment strategies
Who should attend?
- Data Scientists
- Data Analysts
- Data Engineers
- Machine Learning Engineers
- AI architects
What will I learn?
Upon completion of this course, learners will be able to:
- Recognise and detect unwanted Bias in AI system
- Apply measurement techniques and methods to assess bias and fairness
- Mitigate bias-related vulnerabilities
- Control and treat of unwanted bias throughout an AI system life cycle (Design, and Development, Verification and Validating, Deployment
What is included?
On completion, you’ll be awarded an internationally recognized BSI training course certificate.
