Program Overview

B.S. in Data Science Overview

The B.S. in Data Science (BSDS) curriculum provides a solid foundation in the key data science principles and applications necessary to support organizational data needs and strategies. Students will gain proficiency in the fundamentals of data science programming, mathematical and analytical algorithms, data systems and pipelines, and data visualization and presentation.

Learning Outcomes

Pursuing a B.S. in Data Science will prepare you to become an expert in the field and work at the cutting edge of a new discipline. According to LinkedIn’s most recent Emerging Jobs Report, data science is booming and data scientist is one of the top three fastest-growing jobs. A B.S in Data Science from the University of Virginia opens career paths in public or private industry. Graduates of our program will:

• Identify, formulate, and solve complex problems by applying principles of data analytics, mathematics, systems, value, and design
• Effectively communicate data products and findings to a range of audiences
• Assess and diagnose ethical and professional conflicts in data science to make informed judgments
• Appreciate the benefit of diverse perspectives when working within and leading data science teams
• Lead and complete data-driven projects by establishing clear goals, planning tasks, and meeting objectives

The B.S. in Data Science degree program will require 120 credit hours. A final project course will be required. The Undergraduate Record represents the official repository for academic program requirements.

Program Requirements

Prerequisites for Admission

The BSDS program has prerequisites of the following two courses, which must be completed or in progress at the time of application:

• DS 1001: Foundation of Data Science (3 credits)
• DS 1002: Programming for Data Science (3 credits)

Both courses are offered in the fall and spring semesters, do not have prerequisites, and may be taken concurrently. Students interested in pursuing the BSDS program must take both courses in their first-year to be eligible to apply.

BSDS Curriculum

Once admitted to the program, BSDS students will follow a three-year curriculum. Courses used to satisfy requirements in the Data Science Minor (DS 2002, DS 2003, DS 2004, DS 3001, & DS 4002) do not fulfill requirements in the B.S. of Data Science.

First Year of Major: Understand

• Fall:
  • DS 2022 – Systems I: Intro. to Computing
  • DS 2023 – Design I: Communicating with Data
  • DS 2026 – Computational Probability
  • MATH 1190/1210/1310 or APMA 1090 – Calculus I*
• Spring:
  • DS 2024 – Value I: Ethics & Policy in Data Science
  • DS 3021 – Analytics I: Machine Learning
  • DS 3025 – Mathematics for Data Science

Second Year of Major: Apply

• Fall:
  • DS 3022 – Data Engineering
  • DS 4021 – Analytics II: Machine Learning
• Spring:
  • DS 3026 – Principles of Inference & Prediction
  • DS 4320 – Data by Design
  • DS 4024 – Value II: Explainable AI

Third Year of Major: Analyze, Evaluate, Create

• Fall:
  • Concentration Course
  • Concentration Course
  • Concentration Course
• Spring:
  • DS 4022 – Data Science Project
  • 2nd Concentration Course (Optional)
  • 2nd Concentration Course (Optional)

Concentrations

Tailor your degree to match your interests and career goals with one or more dynamic concentrations. These concentrations not only prepare you for industry roles and research opportunities, but also empower you to make your degree as unique as your ambitions.

All students will select at least one core concentration from the School of Data Science. Students may elect to pursue multiple concentrations, including adding a collaborative concentration. All concentrations require 3 classes/ 9 credits; students may not double-count courses across concentrations.

• School of Data Science Core Concentrations
  • Analytics
  • Systems
  • Design
  • Value
• Collaborative Concentrations
  • Accounting Analytics
  • Astronomy
  • Educational Analytics
  • Environmental Science
  • Human Movement and Physiology
  • Mathematics
  • Neuroscience

General Education Requirements

First-year prospective BSDS students are advised to stay on track with the curricular requirements of their home school; any course completed that does not count toward the School of Data Science's General Education Requirements will count toward overall degree credits. Additionally, we strongly encourage first-year students to take their First Writing Requirement and Calculus I.

Careers in Data Science

According to the U.S. Bureau of Labor Statistics, employment of data scientists is expected to grow by 36% over the next decade with about 20,800 annual job openings. The B.S. in Data Science prepares students to become experts in the field, work at the cutting edge of a new discipline, and thrive in a data-centric world.

In addition to UVA Career Center, students in the BSDS have access to the School of Data Science's career resources, including:

• One-on-one career coaching
• Workshops to prepare for the internship and job search
• Industry-led technical talks
• Career development series specific to BSDS students
• Access to professional development funds
• Faculty mentoring

The School of Data Science offers various resources to support students in their academic and professional pursuits. With a strong focus on career development and industry connections, the program provides students with the skills and knowledge necessary to succeed in the field of data science.