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QS Rank:

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61

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Duke University

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North Carolina

United States

The Master of Science in Data Science and Analytics at Duke University is a premier program meticulously designed to equip students with the essential skills and knowledge for navigating the rapidly evolving field of data science. This program, offered by the esteemed Trinity College of Arts and Sciences, provides a comprehensive curriculum that spans a wide range of topics in data analysis, machine learning, and statistical modeling. With a focus on practical application, students engage in real-world projects that prepare them not only to understand data but also to derive actionable insights through advanced analytical techniques.

Throughout the 24-month program, students will encounter a rigorous coursework framework that includes foundational subjects such as Data Mining, Statistical Methods, Machine Learning, and Data Visualization. The curriculum is designed to build a solid foundation in statistics while offering specialized courses that delve into predictive analytics, big data technologies, and ethical considerations in data use. Students will also have the opportunity to participate in hands-on projects that foster collaboration and innovation, ensuring they graduate with a robust portfolio that showcases their capabilities.

One of the distinguishing factors of this program is the expertise of the faculty. The teaching staff comprises seasoned professionals and distinguished researchers with extensive experience in the data science industry. Their commitment to student success is evident through their personalized teaching methodologies and mentorship programs which guide students in their academic and professional journeys. The faculty members actively engage in groundbreaking research, providing students with exposure to cutting-edge developments in the field and opportunities to contribute to impactful projects.

In addition to a rigorous academic framework, the Master of Science in Data Science and Analytics at Duke University offers outstanding research opportunities and resources. Students have access to state-of-the-art laboratories and data analytics tools that facilitate hands-on learning experiences. The program encourages collaboration with industry partners, allowing students to undertake internships and participate in real-world projects that bridge the gap between academia and the professional realm. These experiences not only enhance learning but also significantly improve employability and job readiness upon graduation.

The career pathways available to graduates of the program are expansive and promising. Prospective job roles include Data Scientist, Business Analyst, Financial Analyst, Marketing Manager, and more specialized positions such as Statistician and Actuary. The program boasts a median base salary of approximately $112,500, reflecting the high demand for skilled professionals in the data science field. Alumni from this program have successfully secured positions at leading organizations, underscoring the efficacy of the curriculum and the university's strong industry connections.

Furthermore, the program has garnered testimonials from numerous alumni who attribute their success to the comprehensive education and experiential learning opportunities offered at Duke. Their stories reflect a common theme of gratitude towards the faculty, the curriculum’s relevance to industry needs, and the supportive community that fosters both academic and professional growth. With an acceptance rate of 15%, the program attracts talented individuals from diverse backgrounds, contributing to a rich learning environment that enhances collaboration and innovation.

Why Study Master of Science in Data Science and Analytics at Duke University

  • A comprehensive curriculum that balances theoretical knowledge with practical applications in data science.
  • Access to world-class faculty who are experts in their fields and committed to student mentorship.
  • Robust research opportunities with cutting-edge technology and resources that enhance learning experiences.
  • Strong industry connections leading to internships and employment opportunities in top-tier organizations.
  • Diverse and inclusive international community fostering global perspectives and collaborative learning.
  • A high median base salary of approximately $112,500, reflecting the program’s strong return on investment.
  • Alumni success stories that demonstrate the program's impact on career advancement and professional growth.

To be eligible for the Master of Science in Data Science and Analytics, applicants must possess a relevant undergraduate degree and submit standardized test scores, such as the GRE. A minimum GRE score of 329 is recommended, along with strong performance in quantitative sections. Additionally, proficiency in English is required, evidenced by scores from standardized tests like the IELTS (minimum score of 7.0) or TOEFL (minimum total score of 90). Other application materials include a statement of purpose, a resume, and a valid passport. The application deadline for the Fall intake is set for April 1st, 2025.

In conclusion, the Master of Science in Data Science and Analytics at Duke University represents an exceptional educational opportunity for aspiring data professionals. With its rigorous curriculum, expert faculty, extensive research opportunities, and strong industry connections, this program is grounded in preparing students for success in a competitive job market. Join a vibrant community of learners dedicated to making meaningful contributions in the world of data science.

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Total Tuition Fees

$32,560

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Duration

24 Months

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Median Salary

$1,12,500

Ranking

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#10

US World and News Report

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#25

The World University Rankings

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#61

QS World University Rankings

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Intake

Fall ( Sept - Nov )

Class Profile

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Class Size

40

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Average Age

28

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Average Work Experience

3 Years

Diversity

International:

10%

White American:

48%

African American:

14%

Native American:

1%

Hispanic American:

10%

Asian American:

17%

Career Outcomes

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Median Earnings After Graduation

$1,12,500 / year

Prospective Job Roles

Financial Analyst

Statistician

Economist

Software Engineer

Data Scientist

Marketing Manager

Business Analyst

Actuary

Top recruiters

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Eligibility Criteria

English Proficiency Tests

  • IELTS

    7

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  • TOEFL

    90

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Standardised Test Score

  • GRE

    329

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Application Requirements

Here's everything you need to know to ensure a complete and competitive application—covering the key documents and criteria for a successful submission.

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Application Fee: 95

  • intake

    Transcript

  • intake

    Resume

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    GRE

  • intake

    IELTS

  • intake

    Statement of Purpose

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    Academic LOR

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    Professional LOR

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    TOEFL

Application Deadlines

Standard Deadline
FallApr 1, 2025

Fees and Funding

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Tuition Fees

$65,120 / year

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Overall Cost

$90,000 / year

Funding Options

Department Funding

External Sources - Scholarships

Scholarships

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    The Duke University Scholarship

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    Duke University Alumni Scholarship

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    The Duke University Office of Financial Aid

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    Duke University School of Engineering

FAQs

  • Many students choose to move to Durham in July or early August in order to get situated before a new semester begins. However, you can move to Durham right up until the day before the first day of school.

  • Yes, you can count six credits of external courses towards your degree. If you need to take more than six credits external to the department and have it count toward the degree, you need to get approval from the Master's Director before registration.

  • All graduate students are eligible to apply for and be appointed as Teaching and/or Research Assistants. Every MS student will have a number of T.A. opportunities, should they be interested; we naturally encourage this interest as part of the professional development program for the MSS.

  • Of course! Our top students come from diverse backgrounds. Critically, all are very well prepared in operational mathematics (calculus & linear algebra), are computationally-oriented, and are problem solvers.

  • Calculus-based probability theory; Calculus-based mathematical statistics; Regression analysis; Matrix algebra. A course on computer programming is highly desirable.

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