Responsible Data Science

4 credits

Data science lifecycle, data cleaning and quality management, data profiling, causal inference, algorithmic fairness (fairness definitions, impossibility results, causal fairness, building fair ML models, fairness beyond classification), algorithmic transparency (interpretability versus explainability, auditing-black-box algorithms, algorithmic recourse). Prerequisites: DSC 210 and DSC 240. Restricted to DSC-MS-001 and DSC-PhD-001 students.