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Data Science, Analytics and Visualization (DS) Learning Outcomes

Upon completion of the undergraduate B.S. program in Data Science, Analytics & Visualization, students will be able to:

  1. Source, describe and curate large data sets (‘Big Data’) that may not be amenable to traditional hardware and software, and conventional statistical analysis including domain and file specific metadata and the tools built around alternatives to tabular relations that allow the use of multimodal data;

  2. Identify, describe and apply foundational mathematical and statistical concepts and operations, including the application of tools such as R, SQL and Python languages, that underlie data sourcing, management, analysis and interpretation;

  3. Develop and implement approaches for effective data translation, dissemination and communication between domains, stakeholders and the public;

  4. Identify and apply basic data modeling, predictive models and visualizations to support decision-making;

  5. Integrate an awareness of ethical issues and collective standards to positively influence the application of data science to service, justice and peace in working towards solutions for societal problems;

  6. Explain, plan and execute data science tasks within multidisciplinary teams;

  7. Execute a domain-specific capstone project addressing a stakeholder-generated use case.