The need for trust in AI has been of importance and one way of achieving it is through mitigating discrimination and bias in machine learning models throughout the AI application lifecycle. This course will give you an overview on the concept of fairness which helps in building trust in AI and how "AI Fairness 360" open source toolkit can help you implement debiasing techniques to measure, understand and mitigate AI bias. Learners will be provided an overview of AI fairness and bias concepts, how to measure bias in models and how to apply fairness algorithms to reduce unwanted bias. It will also walk you through a demo of working of "AI Fairness 360" open source tool kit and using this tool kit on a real-world use-case.
Note: There are hands-on labs included with this course.
IBM Customers and Sellers: If you are interested in investing in your training, please consider the following Individual or Enterprise Subscriptions:
- IBM Learning for Data and AI Individual Subscription (SUBR022G)
- IBM Learning for Data and AI Enterprise Subscription (SUBR004G)
- IBM Learning Individual Subscription with Red Hat Learning Services (SUBR023G)