Data Science Major, BS in Data Science - Bioinformatics Concentration

4 Years On Campus Bachelors Program

University of Tennessee

Program Overview

The Data Science Major, BS in Data Science – Bioinformatics Concentration at the University of Tennessee, Knoxville combines data science with bioinformatics, giving students the analytical, computational, and biological knowledge needed to work with complex biological datasets. The program suits students interested in applying data analysis, machine learning, and computational methods to areas such as genomics, healthcare, biotechnology, agriculture, and biological research.

Curriculum Structure

Year 1: Students establish their foundation in data science through DATA 101: Data Knowledge and Discovery, which introduces data collection, management, visualization, modeling, computing, and ethical issues. They also begin developing the mathematical, statistical, biological, and computational foundations needed for later bioinformatics coursework.

Year 2: Students progress into DATA 202: Data Management and Visualization and DATA 203: Analytical Methods of Data Science, developing skills in data storage, visualization, statistics, machine learning, and optimization. The Bioinformatics concentration adds biological and computational preparation so students can apply data-science methods to biological questions.

Year 3: Students deepen their technical capabilities through subjects such as DATA 304: Data Wrangling, learning to import, clean, transform, and prepare real-world datasets for analysis. Bioinformatics-focused study connects these data skills with biological datasets, genomics, and computational analysis, while advanced coursework develops the ability to interpret complex scientific information.

Year 4: Students consolidate their analytical and communication skills through advanced data-science study, including DATA 401: Visual Analytics, which uses a project-oriented approach to data visualization and exploratory analysis. The Bioinformatics concentration prepares students to apply computational approaches to biological problems and pursue further study or careers in research, industry, and related organizations.

Focus areas: Data analysis, data management, data visualization, machine learning, statistics, optimization, data wrangling, bioinformatics, biological data analysis, genomics, computational methods, and ethical data use.

Learning outcomes: Students develop the ability to collect, manage, clean, analyze, model, visualize, and communicate data; apply statistical and machine-learning methods; use computational approaches to investigate biological datasets; and consider ethical and privacy issues surrounding data.

Professional alignment (accreditation): The University of Tennessee presents the BS in Data Science as an interdisciplinary program designed around workforce-relevant data skills and practical experience. The university's current official program information does not state a specialized professional accreditation for the BS in Data Science – Bioinformatics Concentration.

Reputation (employability rankings): The University of Tennessee identifies data science as a rapidly growing field and states that employment in data-science-related fields is projected to grow by 35% from 2022–2032 on its official program page. No program-specific QS or Guardian employability ranking is stated on the official University of Tennessee program page.

Experiential Learning (Research, Projects, Internships etc.)

The University of Tennessee, Knoxville’s BS in Data Science with a Bioinformatics concentration combines data analysis with biological applications, giving students opportunities to work with real datasets, computational methods, machine learning, genomics, and data visualization. The curriculum is designed around practical experience, while the university also provides access to bioinformatics training, high-performance computing, research support, and genomics resources.

Students can build hands-on skills through these program-specific opportunities:

Bioinformatics concentration: The 12-credit-hour Bioinformatics concentration develops skills for applying data science to biological research and prepares students for industry, research institutions, government agencies, and postgraduate study.
Real-world datasets: Data Science coursework develops practical skills in data wrangling, data management, visualization, modeling, machine learning, and data mining, while the bioinformatics pathway applies these skills to biological data.
Industry experience: CECS partners with industry to provide students with internships, co-ops, capstones, and research projects, giving students opportunities to apply data science skills beyond the classroom.
Bioinformatics computing: UTK Bioinformatics Services provides training in R and Python scripting, Linux software installation, ISAAC high-performance computing, Git/GitHub, containers with Singularity, and Nextflow workflow development.
High-performance computing: Undergraduate research students can access UTK's High Performance & Scientific Computing (HPSC) environment, which provides substantial computing resources for scientific and data-intensive research.
Genomics and sequencing: Students can work within the university's broader bioinformatics ecosystem, which includes the UTIA Genomics Center for the Advancement of Agriculture, Genomics Core Facility, HPSC Genomics and Sequencing Support, and UTIA Genomics Hub.
Computational research: UTK Bioinformatics Services supports work involving genome/transcriptome assembly, gene annotation, differential-expression analysis, variant calling, and small-RNA analysis, providing exposure to authentic bioinformatics workflows.
Collaborative research projects: UTK's former Explore BiGG Data undergraduate research program used multidisciplinary teams combining biology/genomics students, computational students, faculty mentors, and graduate mentors, with hands-on computational training in R and biological data analysis.
AI and advanced computing: UTK's HPSC environment supports data science and artificial-intelligence research and includes GPU resources, while the university's bioinformatics training introduces students to computational workflows used with biological datasets.
Research institutes: The Joint Institute for Computational Sciences (JICS) provides a broader research-computing environment and collaborations involving genome science, bioinformatics, and computational research.

Progression & Future Opportunities

The Data Science BS with a Bioinformatics concentration prepares students to apply data science and bioinformatics skills in industry, research institutions, and government agencies. The concentration is designed to connect computing and data analysis with biological applications, creating pathways into careers at the intersection of data science, genomics, biotechnology, and life sciences.

Career roles: Bioinformatics Analyst, Data Scientist, Computational Biology Analyst, Research Data Analyst.

Career services: The Center for Career Development & Academic Exploration collects graduate outcomes and supports students in career development. The College of Emerging and Collaborative Studies also offers RISE, a career-readiness program that connects students in Data Science and other emerging fields with industry professionals through group and individual mentoring.
Employment statistics and salary: For the University of Tennessee, Knoxville undergraduate Class of 2025, 90.2% were employed or pursuing graduate education within six months; 62.9% were employed and 26.3% were continuing education. The reported median undergraduate salary was $60,060. These are university-wide undergraduate figures and are not specific to the Data Science BS or Bioinformatics concentration.
University–industry partnerships: AI TechX connects UT researchers with industry leaders to develop real-world AI solutions and workforce skills. UT also collaborates with Oak Ridge National Laboratory (ORNL) and the UT Health Science Center on bioinformatics, genomics, precision health, and related research initiatives.
Research and professional networks: Students interested in advanced computational biology can build toward UT's Bredesen Center programs, including Data Science & Engineering and Genome Science and Technology, with research connections involving UT and ORNL.
Long-term accreditation value: The University of Tennessee, Knoxville is institutionally accredited by the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC) to award bachelor's, master's, educational specialist, and doctoral degrees.
Graduation outcomes: UT's latest university-wide data show that 90.2% of the Class of 2025 had a career outcome within six months, including employment or continuing education, providing a broader indication of post-graduation progression rather than a program-specific outcome.

Further Academic Progression: After completing the bachelor's degree, students can pursue graduate study in Data Science & Engineering, Genome Science and Technology, computational biology, bioinformatics, or related fields. At UT, the Bredesen Center offers PhD pathways in Data Science & Engineering and Genome Science & Technology, including research areas such as computational biology and bioinformatics.