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Undergraduate | In-Person

Data Science, BS

As more data and ways of analyzing them become available, more aspects of the economy, society and daily life will become dependent on data. Work across nearly all domains is becoming more data-driven, affecting both the jobs that are available and the skills that are required.

Why Major in Data Science? 

In a world that is ever-increasing in opportunities and challenges presented by the growth of data, data science spans virtually all industries from healthcare, government, technology, nonprofit, education, agriculture and manufacturing. Belmont’s Data Science program prepares students to employ strong analytical, problem-solving, and communication abilities to tackle the challenges that this big data world offers.

In response to the high industry demand, Belmont’s Data Science program has partnered with the top data scientists from leading companies to create a robust curriculum that teaches students the skills and knowledge that employers are looking for.

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Data Science at Belmont

Dr. Christina Davis, assistant professor of data science, brings a unique blend of scientific rigor and creative problem-solving to her role as the director of Belmont’s data science program.

With a background in astrophysics and a passion for teaching, she helps students with an engaging and custom journey into the field, allowing them to use the tools available to solve niche problems they are interested in solving.

What You'll Learn

  • How to interpret large data sets
  • Understand the story that data tells and how to communicate that story to a wide audience
  • Participate in interdisciplinary coursework in the areas of math and computer science that will prepare you to enter this dynamic field in a variety of scientific and industry settings.

Program Details


The data science major leads to a bachelor of science. It requires 128 hours of coursework:

  • BELL core requirements: 53 hours
  • Major requirements (including 6 hours of tool courses and 12 hours of electives): 39 hours
  • Minor requirements: 18 hours
  • General electives: 15 hours

See All Program Requirements

Courses you'll take:

DSC 1010, Introduction to Data Science: This course will introduce students to this field and equip them with some of its basic tools as well as its general mindset. The focus in the treatment of these topics will be on breadth, rather than depth, with an emphasis on problem-based learning. Real data sets from a variety of disciplines will be used. Students who complete this course will learn the steps involved in data collection, exploratory data analysis, modeling, data visualization and effective communication.

MTH 1151, Elementary Statistics for the Sciences: The study of statistical procedures widely used in the sciences. Topics include modeling with probability distributions, multiple regression, analysis of variance, chi-square tests, nonparametric statistics and bootstrapping.

CSC 1110, Programming I: An introduction to computer organization, algorithm development and programming.

CSC 1120, Programming II: A continuation of algorithm development and programming, including basic aspects of string processing, recursion, internal search/sort methods and simple data structures.

DSC 1000, Seminar in Data Science: This course is required for all data science majors and is to be taken during the first spring semester after declaring Data Science as a major. The seminar provides an orientation to the field of data science and the study of data science at Belmont. Students will learn about data science coursework and curriculum, student organizations, research and other extracurricular opportunities for students, careers for data science graduates and graduate study in data science.

MTH 1210, Calculus I: An introduction to analytical geometry, limits, integration and differentiation.

MTH 1220, Calculus II: Further techniques of integration with applications; exponential and logarithmic functions; parametric equations; and sequences and infinite series.

DSC 2010, Statistical Computing: Students will learn to manipulate data and process information using an appropriate programming language (e.g. R, Python). No previous programming experience is assumed. Students will use data from multiple sources including experiments or surveys, local industry/non-profit partners and public data sets. Throughout the course students will analyze data using statistical and data science techniques. Students will become proficient at selecting the data of interest from large tabular sources, and applying sample aggregate functions (e.g. max, mean) as well as more complex statistical tests. Appropriate use of computers and software will be integrated into the laboratory and data analysis experience.

CSC 2020, Database Systems: An introduction to database management system concepts and applications. Students will practice the design and implementation of relational databases and use SQL to make accurate and efficient queries. Students will also work with unstructured, NoSQL databases, and learn the tradeoffs in efficiency and utility between different database paradigms. They will become proficient at accessing and manipulating data, through both direct, command-line interfaces and libraries embedded within more general programming languages.

DSC 4900, Data Science Project and Portfolio: This course provides students with an opportunity to make connections among ideas and experiences gained from foundations in mathematics, computer science and statistics, and apply them to another domain. Students will engage in the entire process of solving a real-world data science project, from collecting and processing actual data, to applying suitable and appropriate analytics methods to the problem, and communicating the results in a clear and comprehensible way. The course will emphasize a good understanding of the foundational knowledge of the core discipline and the domain area and prepares students for future professional endeavors.

Students in Belmont’s Data Science program can enhance their classroom learning by pursuing data science jobs and internships (which are most often paid).

We also offer students opportunities to participate in a data scientist in residence program, data projects and industry office hours from the beginning of their studies to the time that they enter careers and/or graduate school.

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Career Possibilities

  • Data Analyst
  • Business Analyst
  • Business Intelligence Professional
  • Data Engineer
  • Data Scientist
  • Program/Project Manager
  • Statistician

Alumni Testimonial

"I chose to pursue data science at Belmont because of the guaranteed intersectionality it provides. Right now I am working at the intersectionality of tech, creative and education policy, and I couldn't have asked for a better profession that allows me to combine all of my interests into the greater good."

Miracle Awonuga, Class of 2023

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College of Sciences & Mathematics

Spencer Hayes
Admissions Coordinator
(615) 460.6489
Email Spencer