Bachelor of Science in Data Science

4 Years On Campus Bachelors Program

Indiana University Bloomington

Program Overview

The Bachelor of Science in Data Science at Indiana University Bloomington develops the mathematical, programming, statistical, and analytical skills students need to use data and modern AI technologies to solve real-world problems across business, science, healthcare, sports, and technology. Students can tailor their studies through specializations such as Foundational Data Science, Data Systems, Network and Applied Data Science, Data Science Design, Biological and Health Science, Sports Analytics, and Statistics.

Curriculum Structure:

Year 1: Students build the mathematical and programming foundation needed for data science through courses such as CSCI-C 200 – Introduction to Computers and Programming, CSCI-C 241 – Discrete Structures for Computer Science, and MATH-M 211 – Calculus I. They also begin developing the quantitative reasoning needed to understand how data can be represented, analyzed, and used computationally.

Year 2: Students move into core data-science problem solving with CSCI-A 310 – Problem Solving Using Data, MATH-E 201 – Linear Algebra for Data Science, and STAT-S 350 – Introduction to Statistical Inference. This stage strengthens their ability to apply mathematics, statistics, programming, and analytical methods to increasingly complex datasets.

Year 3: Students develop more advanced data-handling and analytical capabilities through courses such as DSCI-D 321 – Data Representation and Processing, DSCI-D 351 – Big Data Analytics, and STAT-S 352 – Data Modeling and Inference. They can also begin focusing their coursework around one of IU's specialist areas, including data systems, network and applied data science, biological and health science, sports analytics, or data science design.

Year 4: Students apply their accumulated knowledge through advanced specialization coursework and the required DSCI-D 498 – Data Science Capstone I and DSCI-D 499 – Data Science Capstone II sequence. The two-semester capstone provides a team-based opportunity to apply data science skills in a real-world setting and complete the degree with substantial practical experience.

Focus Areas: Foundational Data Science, Data Systems, Network and Applied Data Science, Data Science Design, Biological and Health Science, Sports Analytics, Statistics.

Learning Outcomes: Mathematical reasoning, programming, data analysis, machine learning, database design, algorithms, statistical theory, data visualization, big-data analytics, data modeling, and ethical application of data to real-world problems.

Professional Alignment (Accreditation): Not stated: The official IU Bloomington BS in Data Science pages do not identify a professional accreditation such as ABET for this program. The curriculum instead emphasizes industry-relevant skills in data analysis, AI, machine learning, big data, programming, and applied mathematics.

Reputation (Employability Rankings): Official program information: IU states that data science is expected to grow by an average of 15% over the next decade and reports an average yearly salary of more than $110,000 for the field. A specific QS, Guardian, or other employability ranking for the BS in Data Science itself is not stated on the official IU program page.

Experiential Learning (Research, Projects, Internships etc.)

Students in the Bachelor of Science in Computer Engineering at the University of Washington gain practical experience through extensive laboratory work, hands-on design projects, internships, undergraduate research, and industry-sponsored capstone projects. The program provides access to ECE computing labs, specialized research laboratories, makerspaces, virtual computing environments, and advanced facilities where students can develop and test hardware-software systems; these opportunities connect classroom learning with real engineering applications:

EE 478 – Capstone Integrated Digital Design Projects: Students work in groups of three on substantial digital design projects, with previous projects including ultra-low-power mixed-signal sensor chips, energy-efficient computing electronics, and high-performance microprocessor implementations. Students use industry-standard tools to implement and validate their designs.
EE 475 – Capstone Design Experience: Students prototype a substantial project combining hardware, software, and communications, working with embedded processors, programmable logic devices, and emerging platforms while gaining experience in system specification, design, and project management.
Engineering Entrepreneurial Capstone (ENGINE): Through EE 497 and EE 498, students work in teams on real-world problems from industry-sponsored projects, developing collaborative systems engineering, project management, and entrepreneurial skills.
ECE Computing Labs: Students have access to dedicated computing environments including a Windows Computing Lab, Linux Lab, Digital Design Computing Lab, Power Lab, GPU Lab, and virtual labs. The Digital Design Computing Labs support ECE coursework, while Linux and GPU environments can also be accessed remotely.
Software and Digital Tools: UW provides engineering students with UW Software (U Ware) for reduced- or no-cost access to licensed software and a College of Engineering Virtual Desktop Infrastructure (VDI) that provides a Windows desktop environment. Students can also access the department's Linux and GPU computing environments remotely.
Makerspaces and Prototyping: The Dabble Lab and MILL provide 3-D printers, laser cutters, tools for printed circuit board and interactive-electronics work, and collaborative workspace, allowing students to prototype and experiment with physical computing projects.
Interdisciplinary Engineering Building: The IEB provides classrooms, teaching labs, project-team rooms, student-organization spaces, a machine shop, testing studio, and collaborative learning areas. It also houses the Career Center @ Engineering, where students can receive résumé feedback, professional-development support, and internship assistance.
Research Laboratories: UW ECE has more than 50 department laboratories, allowing undergraduates to work with faculty on research. Research environments include the Center for Neurotechnology, Clean Energy Institute, Institute for Nano-Engineered Systems, Molecular Engineering and Sciences Institute, Northwest Quantum Nexus, and UW QuantumX Initiative.
Undergraduate Research: Students can pursue hands-on research in UW ECE laboratories, including opportunities through the Center for Neurotechnology Research Experience for Undergraduates, where students participate in immersive research, courses, and workshops.
Internships: UW ECE reports that 69% of undergraduate ECE students pursue at least one internship, giving students an opportunity to gain professional experience before graduation.
Industry Experience: UW ECE's industry-facing opportunities connect students with organizations through sponsored projects and professional experiences, while UW Engineering identifies major partners including Microsoft Research, Google, Amazon, and UW Medicine.
Advanced Semiconductor Facilities: Students can gain exposure to semiconductor fabrication through the Washington Nanofabrication Facility, while UW ECE has also introduced virtual-reality training to prepare students for hands-on cleanroom work.

Progression & Future Opportunities

Graduates of the Bachelor of Science in Data Science at Indiana University Bloomington develop mathematical, programming, analytical, and AI-related skills that prepare them to solve data-driven problems across technology, business, healthcare, science, and other sectors. IU’s Luddy School reports that the 2024–25 Data Science graduating cohort recorded 100% successful graduation outcomes, covering full-time employment or graduate-school admission, with graduates moving into technical and business-focused data roles.

Typical Job Roles: Data Engineer, SAP Consultant, Business Systems Analyst, Technical Solutions Consultant.

Career Development & Industry Connections: Students benefit from Luddy’s dedicated career services, employer connections, real-world projects, and opportunities to build experience that supports progression into the data and technology workforce:

Luddy Career Services: Students receive career support focused on connecting them with employers and opportunities in technology, information, and engineering, including career preparation and access to employment opportunities.
Employment & Salary: The 2024–25 Data Science cohort reported an average full-time salary of $79,384, based on 13 reported salaries, and 100% successful graduation outcomes for employment, military service, or continuing education.
Employer Connections: Companies reported by Luddy as having hired Data Science graduates include Ernst & Young, Epic Systems, ION Group, and Inspire11, demonstrating opportunities across consulting, healthcare technology, financial technology, and data services.
Real-World Experience: IU states that Data Science students gain hands-on experience through real research projects, helping them build practical skills and strengthen their résumés before entering professional employment or further study.
Graduation Outcomes: Luddy reports 100% successful graduation outcomes for its Data Science BS Class of 2024–25, while the program specifically prepares students for careers such as data scientist, data manager, researcher, and developer.
Long-Term Professional Value: The degree develops skills in artificial intelligence, machine learning, visualization, applied mathematics, database design, algorithms, cloud computing, distributed systems, and big data, giving graduates a foundation that can adapt as data and AI technologies evolve.

Further Academic Progression: After completing the BS, students can progress directly into employment or continue their education through IU’s Accelerated M.S. in Data Science, which allows eligible Luddy B.S. Data Science students to complete both degrees in five years. The residential M.S. offers tracks in Applied Data Science, Big Data Systems, Computational and Analytical, and Managerial Data Science, while students seeking research-intensive careers can also consider further graduate study.