Drive innovation through data
There is a growing demand in companies and institutions all over the world for professionals who can harness data to solve complex problems. Their insights are used for everything from predicting a company’s customer retention rate to identifying anomalies in DNA structure to measuring the spin rate of a Major League Baseball pitcher’s curveball. The applications of data science are numerous, and this program positions you to take advantage of the field’s incredible career growth.
Our curriculum exists at the intersection of statistics, mathematics, computer science and domain knowledge. The program was designed from the ground up, with feedback from industry professionals, to ensure that students not only understand the mathematical and statistical foundations of data science, but also how those principles may be applied to cutting-edge tools and technologies. This means our graduates will never fall behind the curve as the industry rapidly advances.
All data has context. A keystone of Quinnipiac’s data science major is understanding that context and integrating it with deep technical knowledge to draw meaningful conclusions. With our specially tailored curriculum, students may easily acquire a second major (e.g., economics, mathematics, industrial engineering, biology, etc.) and link those studies to data science through a capstone project. This means that you do not need to “sacrifice” your passion to gain relevant quantitative skills.
You’ll develop a deep understanding of methods in quantitative analysis, predictive modeling and advanced machine learning while mastering the Python programming language and cutting-edge statistical packages in practical, project-driven courses. This range of expertise is vital to employers in finance, health care, technology services, manufacturing, e-commerce, sports, retail trade and just about every other industry. Alternatively, these same skills can prepare you to succeed in graduate studies on data science itself or in related domains.
Field-based experience is a hallmark of this program. Thanks to our vast alumni network and deep industry connections, you’ll have the opportunity to intern at a range of leading companies, including BlackRock, Morgan Stanley, MSCI, Citi, Travelers Insurance, and Pratt & Whitney. Additionally, our unique partnership with Corvinus University in Hungary enables you to take part in year-long business-related projects onsite in Budapest, as well as work at the BlackRock@Corvinus Innovation and Technology Lab.
Unlocking big data’s possibilities
James Soda, assistant professor of mathematics and a data scientist, enjoys applying mathematics and data in new ways to solve complex, real-life problems.
“I’m a curious person,” Soda said. “Data science gives me the room to explore different subjects.”
Data science is valuable in many professional disciplines, including economics, business, natural and applied sciences, and the humanities, where data extraction and analysis can be used to study language patterns in literature, or even, changes in human behavior over time.
“What makes our program unique is that it strikes a balance between a rigorous mathematical base and applied skills,” Soda said. “Part of data science is understanding how to connect one field with tools from other fields.”
This flexibility is exactly what Soda envisioned when he helped develop Quinnipiac’s BS in Data Science. A big part of the program’s foundation is how algorithms are used. For example, grocery store chains and online retailers such as Amazon examine our buying patterns to help predict future purchases. Likewise, Netflix and other streaming services suggest new TV shows based on our viewing history.
“These outcomes are made possible by algorithms developed by data scientists,” he said. “Industries are becoming increasingly aware of the power they have in data.”
As established industries grow and new ones emerge because of data, Soda believes that wherever his students land, they’ll be able to apply the critical thinking skills they learned at Quinnipiac.
“Our program prepares students for success not just today, but five years from now,” Soda said.
Faculty dedicated to student success
Quinnipiac’s College of Arts and Sciences professors are committed to the personal and professional success of every student. While our professors are passionate scholars and accomplished in their own fields, they make teaching their number one priority. Small class sizes, accessible professors with significant industry experience and a close-knit, diverse community create the kind of supporting, enriching environment that is rare. We are personally invested in seeking ways to help our students develop into strong, leading professionals.
Curriculum and Requirements
Data Science Program of Study
- DS 110 Intro to Data Science (3 credits)
- CSC 110/L Intro to Programming (4 credits)
- DS 201 Python (3 credits)
- MA 151 Calculus 1 (4 credits)
- MA 229 Linear Algebra (3 credits)
- MA 285 Intro to Statistics (3 credits)
- EC 365 Econometrics (3 credits)
- DS 210 Algorithms for Data Science (1 credit)
- DS 380 Data Mining (3 credits)
- DS 385 Machine Learning (3 credits)
- DS 480 Senior Seminar (3 credits)
Data Science Electives (6-8 credits)
Take two courses from the following list
- MA 153-154 Calculus II (2 credits)
- MA 251 Calculus III (4 credits)
- DS 215 Communication with Data (3 credits)
- EC 366 Advanced Econometrics (3 credits)
- DS 325 Database Systems (3 credits)
- DS 350 Programming and Big Data (3 credits)
Additional course details
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