Bachelors of Data Science

Program Overview

The Bachelor of Data Science program at Franklin College is an innovative, interdisciplinary field that strategically combines the analytical power of mathematics and computing with a chosen area of application. This program is designed to equip students with the technical skills necessary for data science, alongside the self-awareness and professional disposition essential for career success. Right from the outset, students engage in hands-on projects, building skills in popular programming languages like Python and being introduced to key data science concepts such as machine learning. The program's core goal is to prepare individuals to extract meaningful insights from the vast amounts of data collected daily, enabling informed decision-making across diverse fields.

Curriculum: The curriculum of the Data Science program at Franklin College is developed in close consultation with industry leaders, ensuring its relevance to the modern workplace. Students learn to code in Python and are introduced to machine learning from the very beginning. Beyond technical skills, the program includes a unique course, "Data Equity and Bias," which focuses on the ethical implications of data science, examining how discriminatory bias can infiltrate algorithmic systems and how to approach projects from an equity perspective. Core courses delve into data structures, database design, calculus, linear algebra, probability theory, and statistical consulting. The hands-on, project-based approach ensures students are continually applying what they learn to real-world datasets.

Research Focus: A significant aspect of the Data Science program is its strong emphasis on research and real-world application. Every data science major at Franklin College completes a full data science project using a dataset of their choice right from the outset. As they progress, students undertake larger projects, culminating in a Senior Competency Practicum and a Data Science Capstone. The capstone project allows students to lead a major data science project related to their chosen field of application, guiding the process from problem definition and data collection to model building and analysis. Additionally, all data science majors complete a statistical consulting project, partnering with non-profit organizations from the greater Indianapolis area to answer data-based questions relevant to their missions. This extensive research experience equips students with invaluable skills in data analysis, problem-solving, and professional communication.

Industry Engagement: The Data Science program at Franklin College demonstrates strong industry engagement through several key initiatives. The program was designed in close consultation with business and community leaders in the field, ensuring its curriculum meets industry demands. A key component of the program is the "Big Data and the Professional Workplace" course, where students partner with a team of students and a Franklin College alumnus who works with big data for a semester-long project, gaining valuable experience and industry connections. Furthermore, every data science major is required to complete at least one internship. These internships often lead directly to full-time jobs after graduation, with past students interning at companies like Beckman-Coulter Life Sciences, B2S Life Sciences, and Cummins, providing critical real-world experience and networking opportunities.

Global Perspective: While specific Data Science-focused study abroad programs are not exclusively detailed, Franklin College broadly promotes a global perspective through its Office of Global Education. Students across all disciplines, including Data Science, are strongly encouraged to participate in month-long Immersive Term study away courses, semester or year-long programs at partner universities, or international internships. The college actively works to make study abroad accessible through exchange partnerships and scholarships. These global experiences allow Data Science students to broaden their understanding of how data is used and analyzed in different cultural and economic contexts, fostering intercultural competencies and preparing them for the increasingly global nature of the data science field.