Data science is an interdisciplinary field with roots in applied mathematics, statistics and computer science. The Bachelor of Science in Data Science seeks to meet the increased employment demands across many industries and research fields.
Data Science majors will develop quantitative and computational skills to solve real-world problems. For example, data scientists are responsible for creating and maintaining dashboards in a pandemic, predicting traffic patterns to improve driver safety and helping apps like Uber Eats optimize food delivery. Students can customize the degree to fit their interests by selecting a focus area of their choice to create a degree with practical applications.
Working with their academic advisers, data science students will take classes in a discipline related to their interests and career goals. Students can choose their area of emphasis among a variety of areas including the social sciences, humanities, and sciences. Examples, include astronomy, biology, criminology, geography, geology, GIS, physics, public health, psychology, and sociology.
Major Learning Outcomes
Data Science
Learning Outcome 1: Students will communicate data science workflows in both written and oral forms.
Outcome 1.1 Students will demonstrate their ability to develop and use appropriate data science techniques to address ‘science’ (subject matter) topics and questions.
Outcome 1.2 Students will communicate the biases and other implications of the data and analysis.
Outcome 1.3 Students will prepare a clear and concise written project and orally present a data science workflow and analysis effectively and professionally.
Learning Outcome 2: Students will understand and demonstrate the programming and technological aspects of a data science workflow
Outcome 2.1 Students will develop workflows using the languages and platforms common in data science practice (eg. R and Python, Rstudio and JupyterLab)
Outcome 2.2 Students will demonstrate their ability to acquire and manipulate data via a variety of platforms (eg. databases to cloud computing)
Outcome 2.3 Students will demonstrate their ability to use technologies for collaboration (eg. Git and GitHub)
Learning Outcome 3: Students will demonstrate their ability to visualize and model data
Outcome 3.1 Students will demonstrate visualization of data from simple plots for smaller data sets to visualizations for big data
Outcome 3.2 Students will demonstrate their ability to use current machine learning and other data science modeling methods appropriately and understand the underlying statistical and mathematical concepts.
