M.S. in Accounting
Duquesne University's M.S. in Accounting program stands as a beacon of excellence, ...
B.S. in Data Science
Pittsburgh
INTAKE: Jan & Aug
Program Overview
The B.S. in Data Science at Duquesne University is designed to equip students with the skills necessary to analyze and interpret complex data sets. This interdisciplinary program combines elements of computer science, statistics, and domain knowledge, preparing graduates for the increasingly data-driven world. Students learn how to extract meaningful insights from data, making them invaluable in a wide range of industries. The curriculum emphasizes practical applications, ensuring that students can apply theoretical concepts in real-world scenarios.
Curriculum: The curriculum for the B.S. in Data Science is robust and multifaceted, featuring core courses in programming, statistical analysis, and data visualization. Students take classes such as Introduction to Data Science, Data Mining, and Machine Learning, along with electives that allow them to specialize in areas like big data analytics, artificial intelligence, and business intelligence. Hands-on projects and labs are integral to the learning experience, enabling students to work with actual data sets and develop their analytical skills.
Research Focus: Duquesne University encourages students to engage in research within the B.S. in Data Science program. Students have the opportunity to collaborate with faculty on innovative projects that address real-world problems using data analysis. Research topics may include predictive modeling, natural language processing, and data ethics. This focus on research not only enhances the learning experience but also prepares students for advanced studies or research roles in their future careers.
Industry Engagement: The program emphasizes strong industry engagement by fostering partnerships with local businesses and organizations. Duquesne University provides students with opportunities for internships and cooperative education experiences, allowing them to gain practical knowledge and establish professional networks. These experiences are critical for students as they prepare to enter the workforce, helping them to apply their classroom learning in practical settings and understand industry expectations.
Global Perspective: The B.S. in Data Science program promotes a global perspective by addressing the ethical implications of data use in various cultural contexts. Students are encouraged to consider global data challenges, such as privacy, security, and data governance. Opportunities for study abroad and participation in global research initiatives further enhance this perspective, preparing graduates to work effectively in an increasingly interconnected world.
Location
Pittsburgh
Score
IELTS 6
Tuition Fee
USD 47146
Undergraduate Entry Requirements
Academic Qualifications: Applicants for undergraduate programs typically require a minimum academic achievement of 70% or above in their previous academic qualifications.
English Language Proficiency:
- IELTS: Overall band score of 6.0 with a minimum of 5.5 in each component.
- TOEFL: Overall score of 70 or higher.
- PTE: Overall score of 48 or higher.
- DET (Duolingo English Test): Minimum score of 95.
Scholarships for International Students
International Freshman Scholarships: Duquesne University offers merit-based scholarships for international freshmen based on academic achievements. These scholarships can significantly contribute to tuition expenses.
Spiritan Scholarships: The Spiritan Scholarship is a prestigious award for academically accomplished students who demonstrate a service and leadership. This scholarship aims to support students who align with the university's mission.
Phi Theta Kappa Scholarship: Transfer students who are members of the Phi Theta Kappa Honor Society may be eligible for this scholarship. It recognizes academic excellence and leadership at the community college level.
ESL Merit Scholarships: Duquesne University provides merit-based scholarships for international students enrolled in the English as a Second Language (ESL) program. These scholarships recognize academic achievement and language proficiency.
Global Leaders Scholarship: The Global Leaders Scholarship is designed for international students who have demonstrated leadership qualities and a commitment to making a positive impact on their communities. It supports students who embody the values of global citizenship.
External Scholarships: Duquesne University encourages international students to explore external scholarship opportunities, including those provided by governments, foundations, and private organizations. The university's financial aid office can assist students in identifying relevant external scholarships.
Talent-Based Scholarships: In addition to academic scholarships, Duquesne University offers talent-based scholarships in areas such as music, art, and athletics. These scholarships recognize outstanding achievements and contributions in specific fields.
Need-Based Financial Aid: Duquesne University is meeting the financial needs of admitted students. International students with demonstrated financial need may be eligible for need-based financial aid packages.
Graduates with a B.S. in Data Science from Duquesne University are well-equipped to pursue diverse and rewarding careers in the rapidly growing field of data science. The interdisciplinary nature of the program ensures that students develop a broad skill set, making them competitive in various industries.
Data Analyst: Many graduates start their careers as data analysts, where they interpret complex data sets and provide insights to help organizations make informed decisions. They utilize statistical tools and software to analyze trends, patterns, and relationships in data, enabling businesses to optimize their operations.
Data Scientist: Some graduates become data scientists, a role that typically involves more advanced analytical techniques. Data scientists use machine learning algorithms, predictive modeling, and advanced statistical methods to derive insights from data and develop data-driven solutions to complex problems.
Business Intelligence Analyst: Graduates often find roles as business intelligence analysts, where they focus on analyzing data to improve business strategies and operations. They create reports and dashboards to visualize data and communicate findings to stakeholders, driving data-informed decision-making within organizations.
Machine Learning Engineer: With a strong foundation in programming and algorithms, some graduates pursue careers as machine learning engineers. In this role, they design and implement machine learning models and algorithms to automate processes and enhance predictive analytics capabilities.
Data Engineer: Graduates may also work as data engineers, responsible for building and maintaining the infrastructure that allows for the collection, storage, and processing of large data sets. They focus on creating robust data pipelines and ensuring data quality and accessibility for analysis.
Statistician: Some graduates choose to work as statisticians, applying statistical techniques to analyze and interpret data in various fields, including healthcare, finance, and government. They design experiments and surveys, interpret results, and communicate findings to stakeholders.
Quantitative Analyst: In the finance sector, graduates can work as quantitative analysts, using mathematical models and statistical techniques to inform trading strategies and risk management decisions. They analyze financial data and trends to assist organizations in maximizing profits and minimizing risks.
Research Scientist: Graduates may also pursue positions as research scientists, working in academic or corporate research settings to analyze data for scientific studies. They conduct experiments, collect data, and interpret results to contribute to advancements in their fields.
Graduate Studies: Many graduates opt to further their education by pursuing advanced degrees in data science, statistics, artificial intelligence, or related fields. Advanced studies can lead to specialized roles in research, academia, or high-level technical positions.
