Data Science BS

Every day, human interaction with technology generates enormous volumes of data. This ever-growing collection of information is leveraged in virtually every industry across the globe, including healthcare, government, technology, manufacturing, social media, finance and entertainment.

As a data science student, you will learn practical solutions to solve a wide array of data-related problems—from those involving small data sets to those involving massive amounts of data. Your curriculum will incorporate the entire data science pipeline, including problem formulation, data collection, high-powered computing, statistical analyses and meaningful interpretation and communication.

You'll develop proficiency in navigating both the overarching concepts and nuanced details of data science, empowering you to confidently achieve the following objectives:

  • Managing, processing and analyzing data effectively.
  • Using data visualization techniques to extract valuable insights.
  • Creating statistical models and machine learning algorithms to solve complex problems.
  • Interpreting model outputs and making informed decisions.
  • Communicating data findings clearly to diverse audiences.
  • Staying updated on the latest advancements in artificial intelligence (AI).
  • Building a solid foundation for future graduate studies in data science.

Program Information

Duquesne University's Bachelor of Science (B.S.) in Data Science program provides comprehensive training for a variety of careers in technology, finance, healthcare, marketing and more. Gain expertise in the entire data science pipeline, from data collection to cutting-edge model development and implementation and effective communication, while mastering subjects like statistics, machine learning and computer programming.

Program Type

Major

Degree

Bachelor's

School

School of Science and Engineering

Academic Department

Mathematics and Computer Sciences

Duration

4-years

Required Credit Hours

120

Modality

In-Person

Alumni Voices

Apply Today
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"The Department of Mathematics and Computer Science has amazing mentors who helped me flourish in geospatial data science and land a job as a Director of GIS. The many research opportunities set students up for the next stage—whether it's employment or graduate school."

Ethan Shearer, MCS '25
Join the Data Science Program
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"Data science allows you to combine the best parts of math, statistics and computer science to solve problems of all sorts. Even if you don't have any background knowledge in these areas, the professors at Duquesne provide all the tools to help you learn and succeed."

Val Koester, MCS '23
Enroll Now

Data Science FAQs

A data scientist is a professional who analyzes and interprets complex data to uncover insights and trends that can inform business decisions, strategies and solutions. Data scientists use a combination of statistical analysis, machine learning techniques, programming skills and domain knowledge to extract meaning from large datasets.

Data scientists work across various industries, including technology, finance, healthcare and marketing, helping organizations leverage data to optimize processes, improve products and drive innovation.
Absolutely! Students may opt for the dual degree in data science, and our bridges curriculum makes it easy to do! Bridges courses make up approximately one third (more than one year!) of your college curriculum. The best first step is to speak with your Success Coach and let that person know your interest. 
Students receive a comprehensive support system that includes free tutoring services, state-of-the-art computer labs and personalized one-on-one mentoring with our faculty members who are experts in their respective fields. This robust framework is designed to ensure that students not only have access to academic assistance but also benefit from a tailored guidance experience, fostering a rich and engaging learning environment.

Absolutely! If you are not majoring in data science, you can earn a minor in data science. The minor will provide you data analysis and quantitative skills to enhance any degree program. Pursuing a minor in data science entails completing nine additional credits of data science course work and six credits of statistics.

Learn more about the minor

Questions? Contact Us!

Initiate your journey into Data Science today by reaching out to your curriculum coordinator!

Lauren Sugden, Ph.D.

Assistant Professor, Statistics

Mathematics and Computer Science

Engage. Explore. Excel.

 
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Dive Into Meaningful Research

As a Data Science student, you’ll contribute to faculty-led research in areas like machine learning, data analytics, cybersecurity, and mathematical modeling, often collaborating with major institutions and industry partners.

Explore Research Opportunities
internship opportunities

Turn Classroom Learning Into Career Skills

Internships are a key step in building your career. Our program connects students with opportunities at companies of all sizes, non-profits and government agencies, providing hands-on experience that prepares you for future success.

Find Your Internship
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Connect Through Clubs and Organizations

Join a vibrant community of STEM and mathematics enthusiasts through our wide range of student clubs and organizations. With support from faculty and staff, you can connect with like-minded peers, lead events and develop leadership and professional skills.

Join A Club

Expand Your Horizons With A Minor or Certificate

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Choose A Minor or Certificate That Supports Your Bigger Goals

Whether you’re looking to strengthen your current degree with advanced math courses or explore a future in a math-related field, our minors and certificate programs provide the knowledge and skills you need.

 

Summer Undergraduate Research Program

Each summer, you can take part in Duquesne's 10-week Undergraduate Research Program (URP), where you'll conduct hands-on research on funded projects supported by government agencies, non-profit organizations and corporate foundations. These projects often extend beyond campus to include partnerships with experts from major research institutions and industry.

See What URP Offers

Sample Course Work

This is sample coursework for the Data Science BS degree. Please note: Students in the Honors College need to complete 6 honors courses. Bridges Coursework requires students to take one Theology and one Philosophy course. It is recommended to do this as a Bridges Competency course.

Fall Semester (17 credits)
  • General Elective
  • EQ XXX Essential Questions Seminar
  • MATH 115 Calculus I
  • BRDG 101 Writing and Analysis
  • COSC 170 Programming: Python
  • BRDG 100 Research & Info Skills

Spring Semester (16 credits)
  • BRDG 102 Writing and Literature
  • DTSC 110 Intro to Data Science
  • MATH 116 Calculus II
  • COSC 216 Data Structures in Python
  • MATH 135 Discrete Math
Fall Semester (16 credits)
  • DTSC 220 Data Expl & Visualization
  • MATH 215 Calculus III
  • MATH 301 Intro Prob & Stats I
  • BRDG 105 Intro to Ethical Reasoning
  • COMM 250 Technical Communication

Spring Semester (15 credits)
  • THEO xxx Theology Course
  • MATH 302W Intro Prob & Stats II
  • Bridges course - Communication & Creative Expression
  • COSC 300 Algorithms
  • General Elective
Fall Semester (14/15 credits)
  • PHIL xxx Philosophy Course
  • General Elective
  • BIOL 111/L, CHEM 121/L, or PHYS 211/L
  • MATH 325W Applied Stats w/ Regression
  • Experiential Learning course __ (SPRG 108 recommended)

Spring Semester (16/17 credits)
  • MATH 310 Linear Algebra
  • DTSC 330 Big Data & Databases
  • BIOL 112/L, CHEM 122/L, or PHYS 212/L
  • Bridges course - Critical Thinking
  • General Elective
Fall Semester (13 credits)
  • DTSC 140 Professional Development Seminar
  • Bridges course - Ethical Reasoning 
  • Bridges course - Cultural Fluency
  • Bridges course - Social & Historical reasoning
  • General Elective

Spring Semester (15 credits)
  • COSC 423 Machine Learning OR 410 Artificial Intel
  • DTSC 481 Data Science Capstone Project
  • MATH 473 Statistical Computing
  • General Elective
  • General Elective

Learning Outcomes

  1. Write code to gather, clean, integrate, and manipulate data.
  2. Identify trends, patterns, and outliers in real-world datasets using descriptive statistics and visualization techniques.
  3. Identify appropriate machine learning algorithms for a given problem, implement them, and assess their performance.
  4. Identify and perform appropriate statistical tests and explain their output.
  5. Communicate data-driven insights to diverse audiences.

Accreditation

MSCHE is Duquesne University’s institutional accreditor, recognized by the U.S. Department of Education for ensuring the highest standards of academic quality and integrity. This accreditation assures students that their learning experience meets nationally recognized standards of excellence, supports continuous improvement, and strengthens the value of their Duquesne degree both nationally and globally.

Middle States Commission on Higher Education (MSCHE)

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