CO1: Understand the Data Classifications and qualifications. Scientific thinking.
CO2: Understand Data quality issues and data quality metrics.
CO3: Understand and apply the Ethics of data science
Data Classifications and qualifications. Scientific thinking. Creative and Logical thinking.
Complexities in data. Data quality issues and data quality metrics.
Ethics in data science.