Learning Outcomes

The Data Science undergraduate programs cater to a diverse range of individuals, equipping them for roles in business, industry, the public sector, or further studies in academia. This versatility allows students to apply data science solutions across various domains, such as the environment, health, scientific infrastructure, finance, business, and more. The curriculum of our Data Science undergraduate programs is designed to provide students with a combination of foundation in computer science, statistics, and mathematics, foster their data analytics skills, and prepare them for continuous professional growth. There are three baccalaureate programs offered by URI:

B.A. in Data Science

Audience

Double majors with domain areas from colleges outside of Arts & Sciences or departments within A&S to perform data science in a domain area.

Upon completion of a BA in Data Science students will be able to:

  1. Collect, organize, extract, and load numeric and text data in a manner that supports analysis and communication of results with consideration of ethical implications.
  2. Use exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data sets and effectively communicate visually and in written form about data.
  3. Apply various mathematical, statistical, and machine learning methods and data science techniques to solve problems.
  4. Analyze data and design solutions to real-world data-driven problems.
  5. Apply ethical principles in the analysis of data and its impact on society.

B.S. in Data Science (CSC-STA)

Audience

Students interested in full-stack data science, from data collection and cleaning to database design, analysis, and communication. Pursuing graduate school in Statistics, Computer Science, or Data Science.

Upon completion of a BS with CSC-STA track in Data Science, students will be able to:

  1. Collect, organize, extract, and load numeric and text data in a manner that supports analysis and communication of results with consideration of ethical implications.
  2. Use exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data sets and effectively communicate visually and in written form about data.
  3. Design, correctly implement, and apply rigorous statistical and machine learning data science techniques to solve problems.
  4. Conduct analysis to solve relevant real-world data-driven problems with an emphasis on statistical and computer science methods.
  5. Interpret results, run diagnostics, and assess performance and limitations of proposed statistical and computer science models.
  6. Work effectively in teams to design and implement solutions to data analysis problems.
  7. Apply ethical principles in the analysis of data and its impact on society.

B.S. in Data Science (Applied Mathemetics)

Audience

Students interested in working on more theoretical aspects of algorithms and methods used in data science. Pursuing graduate school in Applied Mathematics, Statistics, or Data Science.

Upon completion of a BS with AMS track in Data Science, students will be able to:

  1. Collect, organize, extract, and load numeric and text data in a manner that supports analysis and communication of results with consideration of ethical implications.
  2. Use exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data sets and effectively communicate visually.
  3. Design, correctly implement, and apply rigorous mathematical and data science techniques to solve problems.
  4. Conduct analysis to solve relevant real-world data-driven problems with an emphasis on mathematical methods.
  5. Interpret results, run diagnostics, and assess performance and limitations of proposed mathematical models.
  6. Work effectively in teams to design and implement solutions to data analysis problems.