The Role of Data in AI Auditing

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. This course emphasizes the important role of data in AI auditing. Given AI systems' reliance on their training data, the quality of that data is the foundation for developing reliable AI systems. In this course, discover the stages for training the AI model, such as testing, preprocessing, and selection. Explore techniques for evaluating data quality, focusing on completeness, accuracy, and consistency, such as data profiling, cleansing, and validation. Examine methods for identifying and addressing data bias in AI systems, using statistical methods and visualization tools. Finally, learn about the importance of data integrity and mitigation strategies such as data augmentation and reweighting. Upon completion, learners will have a deeper understanding of data's impact on AI performance and auditing outcomes.