Data Science Reasoning: from the classroom to the workplace
Data science that influences decisions about individuals and society requires more than technical training. Communicating social implications is as vital as an ability to combine algorithms, models, and digital material to find new discoveries. Some academic programs in data science focus solely on science, technology, engineering, mathematics (STEM) courses without addressing the need for skills in interpretation.
The goal of the project is to introduce critical thinking into data practices used to gain insight about human populations. Critical thinking can add depth to existing technical classes as well as spread data fluency throughout the curriculum.
The project builds capacity in non-STEM skills for any analytics, cyber-security, or data science curriculum. Questions of policy and law that are are essential to professional data science practices will be considered. The project is committed to developing data literacy tailored for public sector, civil society, small business, or others who may not traditionally have access to data science labor. To empower organizations with few resources, teaching materials will leverage existing open data sources.